What can @circleci/mcp-server-circleci do?

natural language circleci pipeline querying and inspection, mcp tool schema generation for circleci api endpoints, authenticated circleci api request routing and credential management, circleci workflow and job status polling with structured response formatting, circleci project and organization context discovery, job log retrieval and parsing with structured output, circleci context variable and secret management interface, workflow and pipeline trigger with parameter passing, build artifact discovery and retrieval

@circleci/mcp-server-circleci

MCP ServerFree

A Model Context Protocol (MCP) server implementation for CircleCI, enabling natural language interactions with CircleCI functionality through MCP-enabled clients

Open Source

/ 100

9 capabilities

Capabilities9 decomposed

natural language circleci pipeline querying and inspection

Medium confidence

Exposes CircleCI API endpoints through MCP tools, allowing LLM clients to query pipeline status, workflow details, job logs, and build history using natural language prompts. The server translates conversational requests into structured CircleCI API calls, parsing JSON responses and presenting human-readable summaries back to the LLM for further reasoning or action.

Solves for

Ask an AI assistant about the current status of my CircleCI pipelines without leaving my IDEGet a natural language summary of why a specific job failed in my last buildQuery build history and trends across multiple branches using conversational languageInvestigate pipeline performance bottlenecks by asking about job durations and retry patterns

Best for

Development teams using CircleCI who want to integrate CI/CD insights into AI-powered workflows

Solo developers building LLM agents that need real-time CI/CD status visibility

Teams migrating from REST API polling to MCP-based tool integration for better context management

Requires

CircleCI account with API token (personal or project-level)

MCP-enabled client (Claude Desktop, custom LLM application, or compatible tool)

Node.js 16+ runtime for the MCP server process

Limitations

Depends on CircleCI API availability and rate limits — high-frequency queries may hit throttling

Read-only by default for most query operations; mutation capabilities depend on MCP server configuration

Latency includes network round-trip to CircleCI API plus LLM reasoning time — not suitable for sub-second monitoring

What makes it unique

Implements MCP protocol as a bridge between LLMs and CircleCI, allowing conversational access to CI/CD state without custom API wrappers. Uses MCP's tool registry pattern to expose CircleCI endpoints as callable functions with schema-based parameter validation, enabling the LLM to reason about which API call to make based on user intent.

vs alternatives

Provides tighter LLM integration than CircleCI's native REST API or webhooks because the MCP protocol gives the LLM direct tool invocation with structured responses, versus requiring custom prompt engineering or external orchestration layers.

mcp tool schema generation for circleci api endpoints

Medium confidence

Automatically generates MCP-compliant tool schemas from CircleCI API specifications, mapping REST endpoints to callable MCP tools with typed parameters, descriptions, and return types. The server maintains a registry of available tools that MCP clients can discover and invoke, handling parameter marshaling, request construction, and response parsing transparently.

Solves for

Enable an LLM to discover what CircleCI operations are available without reading API documentationEnsure type-safe parameter passing from LLM tool calls to CircleCI API endpointsAllow MCP clients to dynamically adapt their behavior based on available CircleCI toolsReduce boilerplate in custom integrations by reusing pre-built tool definitions

Best for

Developers building custom MCP clients that need CircleCI integration

Teams standardizing on MCP for multi-tool orchestration across CI/CD and other services

LLM application builders who want declarative tool definitions rather than imperative API calls

Requires

MCP specification knowledge (version 1.0+)

Node.js 16+ with TypeScript support for schema definition

CircleCI API documentation or OpenAPI spec for endpoint mapping

Limitations

Schema generation is static at server startup — changes to CircleCI API require server restart

Complex nested parameters in CircleCI API may not map cleanly to MCP's flat parameter schema

Tool discovery is synchronous and blocking — large tool registries may slow MCP initialization

What makes it unique

Implements MCP's tool discovery and invocation protocol specifically for CircleCI, using a schema-based approach where each CircleCI API endpoint becomes a first-class MCP tool with full type information. This differs from generic REST API wrappers by providing semantic understanding of CircleCI operations at the protocol level.

vs alternatives

More maintainable than hand-coded tool definitions because schema generation is declarative and can be updated centrally, versus alternatives like Zapier or IFTTT that require UI-based configuration for each integration point.

authenticated circleci api request routing and credential management

Medium confidence

Manages CircleCI API authentication by accepting and securely storing API tokens, then automatically injecting credentials into outbound API requests. The server handles token validation, request signing, and error handling for authentication failures, abstracting credential complexity from MCP clients while maintaining security boundaries.

Solves for

Provide CircleCI API access to an LLM without exposing raw API tokens in prompts or logsCentralize credential management so multiple MCP clients can share a single authenticated server instanceAutomatically retry failed requests due to token expiration or rate limitingAudit which CircleCI operations were invoked and by which client

Best for

Teams deploying MCP servers in shared environments where credential isolation is critical

Organizations with strict API key management policies requiring centralized token handling

Multi-user LLM applications where individual users should not manage CircleCI tokens directly

Requires

CircleCI API token (personal or project-scoped)

MCP server running with environment variable or configuration file access

TLS/HTTPS for production deployments to protect credentials in transit

Limitations

Token storage is in-memory by default — credentials lost on server restart unless persisted externally

No built-in token rotation — expired tokens require manual server reconfiguration

Single token per server instance — multi-account CircleCI access requires multiple server deployments

What makes it unique

Implements credential management at the MCP server layer rather than delegating to clients, using a centralized token store that injects authentication into CircleCI API calls. This pattern isolates credentials from LLM prompts and client code, reducing exposure surface compared to passing tokens through tool parameters.

vs alternatives

More secure than client-side token management because credentials never appear in LLM context or logs, and more convenient than OAuth flows because it avoids the complexity of token refresh cycles for server-to-server integrations.

circleci workflow and job status polling with structured response formatting

Medium confidence

Periodically queries CircleCI API for workflow and job status updates, caching results and formatting responses as structured data (JSON) that MCP clients can parse and act upon. The server implements polling logic with configurable intervals, deduplication of unchanged status, and human-readable summaries for LLM consumption.

Solves for

Monitor CircleCI pipeline status in real-time without manually checking the dashboardGet instant notifications when a job fails or a workflow completesBuild dashboards or alerts that react to CircleCI state changesCorrelate CircleCI events with other system events in a unified LLM-driven workflow

Best for

Teams building LLM agents that need to react to CI/CD events autonomously

Developers integrating CircleCI status into broader automation workflows

Organizations that want to avoid CircleCI webhook complexity by using pull-based polling instead

Requires

CircleCI API token with read permissions for workflows and jobs

MCP server with persistent state or external cache for deduplication

Configurable polling interval (default recommended 30-60 seconds)

Limitations

Polling introduces latency — status updates are delayed by the polling interval (typically 10-60 seconds)

High polling frequency increases CircleCI API quota consumption and may trigger rate limiting

No event-driven notifications — missed events between polls cannot be recovered

What makes it unique

Implements pull-based polling as an MCP tool rather than relying on CircleCI webhooks, giving clients explicit control over when and how often to check status. Uses caching and deduplication to minimize API calls while maintaining freshness, with structured response formatting optimized for LLM parsing.

vs alternatives

Simpler to deploy than webhook-based monitoring because it doesn't require inbound network access or webhook registration, making it suitable for LLM applications running in restricted environments. Provides tighter LLM integration than CircleCI's native notifications because responses are structured for programmatic consumption.

circleci project and organization context discovery

Medium confidence

Queries CircleCI API to enumerate available projects, organizations, and their configurations, exposing this metadata as MCP tools that LLM clients can invoke to understand the scope of accessible CircleCI resources. The server caches organization and project lists, allowing clients to dynamically discover which pipelines they can query or interact with.

Solves for

Ask an LLM which CircleCI projects are available without manually listing themAutomatically discover the correct project identifier for a given repository nameUnderstand the organization structure and project hierarchy in CircleCIValidate that a requested project exists before attempting to query its pipelines

Best for

Multi-project organizations where developers need to discover available pipelines dynamically

LLM agents that need to infer the correct CircleCI project from a user's natural language request

Teams building self-service CI/CD dashboards that adapt to organizational structure

Requires

CircleCI API token with organization read permissions

MCP server with caching layer for performance

Limitations

Discovery is read-only — cannot create or modify projects through MCP tools

Caching may be stale if projects are frequently added/removed; requires manual cache invalidation

Large organizations with hundreds of projects may experience slow discovery queries

What makes it unique

Exposes CircleCI's project and organization hierarchy as queryable MCP tools, allowing LLMs to dynamically discover available resources rather than requiring hardcoded project lists. Uses caching to balance freshness with API efficiency.

vs alternatives

More flexible than static configuration because it adapts to organizational changes without server restarts, and more discoverable than requiring users to manually specify project identifiers in prompts.

job log retrieval and parsing with structured output

Medium confidence

Fetches CircleCI job logs via API and parses them into structured formats (JSON, markdown) suitable for LLM analysis. The server extracts key information like error messages, test results, and build artifacts from raw logs, enabling LLMs to reason about job failures without processing unstructured text.

Solves for

Ask an LLM to explain why a specific CircleCI job failed by analyzing its logsExtract test failure summaries from job logs for automated incident reportingSearch job logs for specific error patterns or warningsGenerate human-readable summaries of job execution for debugging

Best for

Development teams that want AI-powered log analysis for faster debugging

Automated incident response systems that need to extract actionable insights from CI logs

Teams building LLM-driven troubleshooting agents

Requires

CircleCI API token with job log read permissions

Job ID or workflow/job name for log lookup

Optional: custom log parsing rules or regex patterns

Limitations

Large job logs (>10MB) may exceed LLM context windows or cause parsing timeouts

Log parsing is heuristic-based and may miss domain-specific error patterns

CircleCI API has log retention limits — old logs may not be retrievable

What makes it unique

Implements log parsing and structuring at the MCP server layer, transforming unstructured CircleCI logs into LLM-friendly formats. Uses heuristic extraction to identify errors, warnings, and test results, reducing the cognitive load on LLMs when analyzing failures.

vs alternatives

More efficient than asking LLMs to parse raw logs because structured extraction happens server-side, reducing token consumption and improving analysis accuracy. Provides better context than CircleCI's native log UI because it surfaces key information programmatically.

circleci context variable and secret management interface

Medium confidence

Exposes CircleCI context variables and secrets through MCP tools, allowing authorized clients to query available contexts and their variable names (but not values, for security). The server implements read-only access to context metadata while preventing exposure of sensitive values in logs or LLM context.

Solves for

Discover which CircleCI contexts are available for a given projectVerify that required environment variables are configured in CircleCI contextsAudit which contexts are used by specific workflows or jobsUnderstand the scope and dependencies of CircleCI secrets without exposing values

Best for

Teams managing complex CircleCI configurations with many contexts and secrets

Security-conscious organizations that need to audit secret usage without exposing values

LLM agents that need to understand configuration dependencies without accessing sensitive data

Requires

CircleCI API token with context read permissions

MCP server with access control enforcement

Limitations

Read-only access to context metadata — cannot create, update, or delete contexts through MCP

Secret values are never exposed (by design), limiting LLM's ability to diagnose configuration issues

Context variable names may themselves be sensitive in some organizations — access control is coarse-grained

What makes it unique

Implements a security-first approach to context variable exposure by providing metadata-only access through MCP, preventing accidental secret leakage into LLM context or logs. Uses CircleCI's API to enumerate contexts while enforcing a strict no-value-exposure policy.

vs alternatives

More secure than exposing context variables directly because values are never transmitted, and more discoverable than requiring manual documentation of available contexts.

workflow and pipeline trigger with parameter passing

Medium confidence

Enables MCP clients to trigger CircleCI workflows and pipelines with custom parameters, handling parameter validation, request construction, and response parsing. The server maps MCP tool parameters to CircleCI's workflow trigger API, supporting both simple parameter passing and complex parameter objects.

Solves for

Trigger a CircleCI workflow from an LLM agent based on user request or automated decisionPass custom parameters (branch, environment, feature flags) to triggered workflowsImplement LLM-driven CI/CD automation that responds to events or user commandsBuild self-service deployment tools where LLMs help users select parameters and trigger builds

Best for

Teams building LLM-driven deployment or release automation

Organizations that want to enable non-technical users to trigger CI/CD workflows through natural language

Developers building autonomous agents that need to trigger builds as part of larger workflows

Requires

CircleCI API token with workflow trigger permissions (write access)

Project and workflow identifiers

Parameter schema definition for validation

Limitations

Requires write permissions on CircleCI projects — security risk if MCP server is compromised

No built-in approval workflow — triggered pipelines execute immediately without human review

Parameter validation is limited to CircleCI API schema — complex business logic validation must be external

What makes it unique

Implements workflow triggering as an MCP tool with full parameter validation and schema enforcement, allowing LLMs to safely trigger builds with custom parameters. Uses CircleCI's workflow trigger API endpoint with structured parameter marshaling.

vs alternatives

More flexible than CircleCI's native UI because parameters can be dynamically determined by LLM reasoning, and safer than raw API access because parameter validation happens server-side before transmission.

build artifact discovery and retrieval

Medium confidence

Queries CircleCI API to enumerate build artifacts (test reports, logs, binaries, etc.) and provides MCP tools for retrieving artifact metadata and download URLs. The server caches artifact listings and handles artifact expiration, enabling LLM clients to discover and reference build outputs without manual dashboard navigation.

Solves for

Ask an LLM to find test reports or coverage reports from a specific buildRetrieve download URLs for build artifacts (binaries, Docker images, etc.) programmaticallyDiscover which artifacts are available from a given workflow or jobIntegrate build artifacts into downstream processes (deployment, analysis, archival)

Best for

Teams with complex artifact management needs across multiple builds

Developers building LLM-driven deployment pipelines that need to reference build outputs

Organizations that want to automate artifact discovery and distribution

Requires

CircleCI API token with artifact read permissions

Job or workflow identifier

Optional: artifact name or path filter

Limitations

Artifact URLs are temporary and expire after CircleCI's retention period (typically 30 days)

Large artifact listings may require pagination — not all artifacts may be discoverable in a single query

Artifact metadata is limited to what CircleCI API exposes (name, size, created time); custom metadata is not accessible

What makes it unique

Exposes CircleCI's artifact API as queryable MCP tools with caching and expiration handling, allowing LLMs to discover and reference build outputs without manual navigation. Handles artifact URL generation and lifecycle management transparently.

vs alternatives

More discoverable than CircleCI's native UI because artifacts are queryable programmatically, and more reliable than hardcoded artifact paths because discovery is dynamic and handles expiration.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with @circleci/mcp-server-circleci, ranked by overlap. Discovered automatically through the match graph.

MCP Server22

CircleCI

** - Enable AI Agents to fix build failures from CircleCI.

mcp-protocol-based circleci tool registration and discoverypipeline status monitoring and latest pipeline retrievalstructured api schema and type definitions for tool inputsbuild failure log retrieval and analysis with context extraction

4 shared capabilities

MCP Server33

@chain-lens/mcp-tool

ChainLens MCP tool — discover sellers, request data, check job status from Claude Desktop and other MCP clients.

authentication and credential management for chainlens api accessmcp tool schema definition and validation

2 shared capabilities

MCP Server27

@zereight/mcp-gitlab

GitLab MCP server for projects, merge requests, issues, pipelines, wiki, releases, and more

ci/cd pipeline status monitoring and artifact retrieval

1 shared capability

MCP Server46

GitLab MCP Server

Manage GitLab repos, merge requests, and CI/CD pipelines via MCP.

ci/cd pipeline inspection and trigger management

1 shared capability

MCP Server20

@mcp-contracts/cli

CLI tool for capturing and diffing MCP tool schemas

cli-based schema workflow automation

1 shared capability

MCP Server24

Hippycampus

** - Turns any Swagger/OpenAPI REST endpoint with a yaml/json definition into an MCP Server with Langchain/Langflow integration automatically.

automatic security scheme extraction and mcp tool binding

1 shared capability

Best For

✓Development teams using CircleCI who want to integrate CI/CD insights into AI-powered workflows
✓Solo developers building LLM agents that need real-time CI/CD status visibility
✓Teams migrating from REST API polling to MCP-based tool integration for better context management
✓Developers building custom MCP clients that need CircleCI integration
✓Teams standardizing on MCP for multi-tool orchestration across CI/CD and other services
✓LLM application builders who want declarative tool definitions rather than imperative API calls
✓Teams deploying MCP servers in shared environments where credential isolation is critical
✓Organizations with strict API key management policies requiring centralized token handling

Known Limitations

⚠Depends on CircleCI API availability and rate limits — high-frequency queries may hit throttling
⚠Read-only by default for most query operations; mutation capabilities depend on MCP server configuration
⚠Latency includes network round-trip to CircleCI API plus LLM reasoning time — not suitable for sub-second monitoring
⚠Requires valid CircleCI API token with appropriate scopes; token rotation not built into the server
⚠Schema generation is static at server startup — changes to CircleCI API require server restart
⚠Complex nested parameters in CircleCI API may not map cleanly to MCP's flat parameter schema

Requirements

CircleCI account with API token (personal or project-level)MCP-enabled client (Claude Desktop, custom LLM application, or compatible tool)Node.js 16+ runtime for the MCP server processNetwork access to CircleCI API endpoints (api.circleci.com)MCP specification knowledge (version 1.0+)Node.js 16+ with TypeScript support for schema definitionCircleCI API documentation or OpenAPI spec for endpoint mappingCircleCI API token (personal or project-scoped)

Input / Output

Accepts: natural language queries, CircleCI project identifiers (org/repo format), workflow or job names, branch names, CircleCI API endpoint definitions, parameter type specifications, authentication credentials, CircleCI API token (string), authentication headers, request metadata, project identifier (org/repo), workflow or job filter criteria, polling interval configuration, organization identifier, project name or slug, filter criteria (e.g., archived status), job ID, workflow name, job name, log filtering criteria, project identifier, context name or filter, custom parameters (branch, environment variables, feature flags), trigger options (e.g., force-trigger), job ID or workflow name, artifact filter criteria (name, path, type), pagination parameters

Produces: structured JSON from CircleCI API, human-readable text summaries, formatted pipeline status reports, job log excerpts, MCP tool schema JSON, tool registry metadata, parameter validation rules, authenticated HTTP requests, error responses with auth context, token validation status, structured workflow status JSON, job status summaries, formatted status change notifications, human-readable status reports, list of projects with metadata, organization configuration, project identifiers and URLs, access control information, raw log text, structured JSON with extracted fields, markdown-formatted summaries, error/warning highlights, list of available contexts, variable names (without values), context scope information, usage metadata, workflow ID, trigger confirmation, workflow URL, parameter echo (for verification), artifact metadata (name, size, created time), download URLs, artifact type information, expiration timestamps

UnfragileRank

Adoption15%(30% weight)

Quality27%(25% weight)

Ecosystem30%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

9 capabilities

Visit @circleci/mcp-server-circleci→

Package Details

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0.15.1

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A Model Context Protocol (MCP) server implementation for CircleCI, enabling natural language interactions with CircleCI functionality through MCP-enabled clients

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Capabilities9 decomposed

natural language circleci pipeline querying and inspection

Medium confidence

Solves for

Best for

Development teams using CircleCI who want to integrate CI/CD insights into AI-powered workflows

Solo developers building LLM agents that need real-time CI/CD status visibility

Teams migrating from REST API polling to MCP-based tool integration for better context management

Requires

CircleCI account with API token (personal or project-level)

MCP-enabled client (Claude Desktop, custom LLM application, or compatible tool)

Node.js 16+ runtime for the MCP server process

Limitations

Depends on CircleCI API availability and rate limits — high-frequency queries may hit throttling

Read-only by default for most query operations; mutation capabilities depend on MCP server configuration

Latency includes network round-trip to CircleCI API plus LLM reasoning time — not suitable for sub-second monitoring

What makes it unique

vs alternatives

mcp tool schema generation for circleci api endpoints

Medium confidence

Solves for

Best for

Developers building custom MCP clients that need CircleCI integration

Teams standardizing on MCP for multi-tool orchestration across CI/CD and other services

LLM application builders who want declarative tool definitions rather than imperative API calls

Requires

MCP specification knowledge (version 1.0+)

Node.js 16+ with TypeScript support for schema definition

CircleCI API documentation or OpenAPI spec for endpoint mapping

Limitations

Schema generation is static at server startup — changes to CircleCI API require server restart

Complex nested parameters in CircleCI API may not map cleanly to MCP's flat parameter schema

Tool discovery is synchronous and blocking — large tool registries may slow MCP initialization

What makes it unique

vs alternatives

authenticated circleci api request routing and credential management

Medium confidence

Solves for

Best for

Teams deploying MCP servers in shared environments where credential isolation is critical

Organizations with strict API key management policies requiring centralized token handling

Multi-user LLM applications where individual users should not manage CircleCI tokens directly

Requires

CircleCI API token (personal or project-scoped)

MCP server running with environment variable or configuration file access

TLS/HTTPS for production deployments to protect credentials in transit

Limitations

Token storage is in-memory by default — credentials lost on server restart unless persisted externally

No built-in token rotation — expired tokens require manual server reconfiguration

Single token per server instance — multi-account CircleCI access requires multiple server deployments

What makes it unique

vs alternatives

circleci workflow and job status polling with structured response formatting

Medium confidence

Solves for

Best for

Teams building LLM agents that need to react to CI/CD events autonomously

Developers integrating CircleCI status into broader automation workflows

Organizations that want to avoid CircleCI webhook complexity by using pull-based polling instead

Requires

CircleCI API token with read permissions for workflows and jobs

MCP server with persistent state or external cache for deduplication

Configurable polling interval (default recommended 30-60 seconds)

Limitations

Polling introduces latency — status updates are delayed by the polling interval (typically 10-60 seconds)

High polling frequency increases CircleCI API quota consumption and may trigger rate limiting

No event-driven notifications — missed events between polls cannot be recovered

What makes it unique

vs alternatives

circleci project and organization context discovery

Medium confidence

Solves for

Best for

Multi-project organizations where developers need to discover available pipelines dynamically

LLM agents that need to infer the correct CircleCI project from a user's natural language request

Teams building self-service CI/CD dashboards that adapt to organizational structure

Requires

CircleCI API token with organization read permissions

MCP server with caching layer for performance

Limitations

Discovery is read-only — cannot create or modify projects through MCP tools

Caching may be stale if projects are frequently added/removed; requires manual cache invalidation

Large organizations with hundreds of projects may experience slow discovery queries

What makes it unique

vs alternatives

job log retrieval and parsing with structured output

Medium confidence

Solves for

Best for

Development teams that want AI-powered log analysis for faster debugging

Automated incident response systems that need to extract actionable insights from CI logs

Teams building LLM-driven troubleshooting agents

Requires

CircleCI API token with job log read permissions

Job ID or workflow/job name for log lookup

Optional: custom log parsing rules or regex patterns

Limitations

Large job logs (>10MB) may exceed LLM context windows or cause parsing timeouts

Log parsing is heuristic-based and may miss domain-specific error patterns

CircleCI API has log retention limits — old logs may not be retrievable

What makes it unique

vs alternatives

circleci context variable and secret management interface

Medium confidence

Solves for

Best for

Teams managing complex CircleCI configurations with many contexts and secrets

Security-conscious organizations that need to audit secret usage without exposing values

LLM agents that need to understand configuration dependencies without accessing sensitive data

Requires

CircleCI API token with context read permissions

MCP server with access control enforcement

Limitations

Read-only access to context metadata — cannot create, update, or delete contexts through MCP

Secret values are never exposed (by design), limiting LLM's ability to diagnose configuration issues

Context variable names may themselves be sensitive in some organizations — access control is coarse-grained

What makes it unique

vs alternatives

More secure than exposing context variables directly because values are never transmitted, and more discoverable than requiring manual documentation of available contexts.

workflow and pipeline trigger with parameter passing

Medium confidence

Solves for

Best for

Teams building LLM-driven deployment or release automation

Organizations that want to enable non-technical users to trigger CI/CD workflows through natural language

Developers building autonomous agents that need to trigger builds as part of larger workflows

Requires

CircleCI API token with workflow trigger permissions (write access)

Project and workflow identifiers

Parameter schema definition for validation

Limitations

Requires write permissions on CircleCI projects — security risk if MCP server is compromised

No built-in approval workflow — triggered pipelines execute immediately without human review

Parameter validation is limited to CircleCI API schema — complex business logic validation must be external

What makes it unique

vs alternatives

build artifact discovery and retrieval

Medium confidence

Solves for

Best for

Teams with complex artifact management needs across multiple builds

Developers building LLM-driven deployment pipelines that need to reference build outputs

Organizations that want to automate artifact discovery and distribution

Requires

CircleCI API token with artifact read permissions

Job or workflow identifier

Optional: artifact name or path filter

Limitations

Artifact URLs are temporary and expire after CircleCI's retention period (typically 30 days)

Large artifact listings may require pagination — not all artifacts may be discoverable in a single query

Artifact metadata is limited to what CircleCI API exposes (name, size, created time); custom metadata is not accessible

What makes it unique

vs alternatives

More discoverable than CircleCI's native UI because artifacts are queryable programmatically, and more reliable than hardcoded artifact paths because discovery is dynamic and handles expiration.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Alternatives to @circleci/mcp-server-circleci

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@circleci/mcp-server-circleci

Capabilities9 decomposed

natural language circleci pipeline querying and inspection

mcp tool schema generation for circleci api endpoints

authenticated circleci api request routing and credential management

circleci workflow and job status polling with structured response formatting

circleci project and organization context discovery

job log retrieval and parsing with structured output

circleci context variable and secret management interface

workflow and pipeline trigger with parameter passing

build artifact discovery and retrieval

Related Artifactssharing capabilities

CircleCI

@chain-lens/mcp-tool

@zereight/mcp-gitlab

GitLab MCP Server

@mcp-contracts/cli

Hippycampus

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @circleci/mcp-server-circleci

Are you the builder of @circleci/mcp-server-circleci?

Get the weekly brief

Data Sources

@circleci/mcp-server-circleci

Capabilities9 decomposed

natural language circleci pipeline querying and inspection

mcp tool schema generation for circleci api endpoints

authenticated circleci api request routing and credential management

circleci workflow and job status polling with structured response formatting

circleci project and organization context discovery

job log retrieval and parsing with structured output

circleci context variable and secret management interface

workflow and pipeline trigger with parameter passing

build artifact discovery and retrieval

Related Artifactssharing capabilities

CircleCI

@chain-lens/mcp-tool

@zereight/mcp-gitlab

GitLab MCP Server

@mcp-contracts/cli

Hippycampus

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @circleci/mcp-server-circleci

Are you the builder of @circleci/mcp-server-circleci?

Get the weekly brief

Data Sources