@contentful/mcp-server
MCP ServerFreeContentful MCP Server - Model Context Protocol server for Contentful
Capabilities7 decomposed
contentful content model introspection via mcp
Medium confidenceExposes Contentful's content type definitions, field schemas, and validation rules through the Model Context Protocol, allowing MCP clients (Claude, other LLMs) to query and understand the structure of a Contentful space without direct API calls. Uses MCP's resource and tool abstractions to map Contentful's GraphQL/REST schema metadata into standardized protocol messages.
Implements MCP protocol as a bridge between Contentful's REST/GraphQL APIs and LLM context, using MCP's resource and tool abstractions to expose schema metadata in a standardized, client-agnostic format that works across any MCP-compatible LLM host
Provides native MCP integration for Contentful without requiring custom API wrappers or prompt engineering to teach LLMs your schema, enabling direct protocol-level interoperability with Claude and other MCP clients
contentful entry creation and mutation via mcp tools
Medium confidenceImplements MCP tools that allow MCP clients to create, update, and delete Contentful entries by invoking standardized tool calls with validated field payloads. Uses Contentful's Content Management API under the hood, with schema validation against the space's content types to ensure only valid entries are submitted. Tool definitions are dynamically generated from the space's content model.
Dynamically generates MCP tool definitions from Contentful content types, enabling schema-aware entry creation where the LLM understands field constraints (required fields, field types, references) at tool invocation time rather than discovering them through trial-and-error
Safer than raw CMA API access because MCP tool schemas enforce field validation before submission, and more flexible than static Contentful UI because it allows LLMs to generate entries programmatically with natural language reasoning
contentful entry querying and filtering via mcp
Medium confidenceExposes Contentful entries through MCP resources and tools that support filtering, sorting, and pagination without requiring direct API calls. Translates MCP query parameters into Contentful's query syntax (Content Delivery API filters), returning structured entry data with resolved references and metadata. Caches frequently accessed entries to reduce API quota usage.
Implements MCP resource discovery for Contentful entries, allowing clients to browse and filter entries through standardized MCP resource URIs rather than learning Contentful's query syntax, with built-in caching to optimize API quota usage
More efficient than raw CDA API calls because it abstracts query complexity into MCP tool parameters and caches results, and more discoverable than direct API access because MCP clients can enumerate available resources and filters
contentful asset management via mcp
Medium confidenceProvides MCP tools and resources for uploading, listing, and managing Contentful assets (images, documents, media files). Handles file upload to Contentful's asset API, generates asset metadata (URLs, dimensions, MIME types), and allows querying assets by type or tag. Supports both direct file uploads and URL-based asset creation.
Wraps Contentful's asset API in MCP tools with automatic metadata extraction (image dimensions, MIME types) and supports both direct file uploads and URL-based asset creation, enabling LLMs to manage media without understanding Contentful's asset processing pipeline
Simpler than raw asset API because it abstracts upload complexity and automatically extracts metadata, and more flexible than Contentful's UI because it allows programmatic asset creation and tagging through natural language
mcp protocol server lifecycle and configuration management
Medium confidenceImplements the MCP server specification, handling client connection negotiation, capability advertisement, and request routing. Manages configuration (API keys, space IDs, environment variables) through environment variables or config files, with support for multiple Contentful spaces. Implements proper error handling and logging for MCP protocol compliance.
Implements full MCP server specification with support for multiple Contentful spaces and environment-based configuration, enabling seamless integration with MCP clients like Claude Desktop without custom server code
Follows MCP standard protocol, making it compatible with any MCP client (Claude, custom hosts), whereas custom Contentful integrations require client-specific code and don't benefit from MCP ecosystem tooling
contentful localization and environment support via mcp
Medium confidenceExposes Contentful's multi-locale and multi-environment capabilities through MCP, allowing clients to query and create entries in specific locales and environments. Handles locale fallback chains and environment-specific API endpoints. Tool definitions adapt based on configured locales and environments.
Adapts MCP tool definitions dynamically based on configured locales and environments, allowing LLMs to understand which locales and environments are available without hardcoding locale lists in prompts
More discoverable than raw CMA API because MCP clients can enumerate available locales and environments, and safer than direct API access because locale/environment validation happens at the MCP layer
contentful webhook and event integration via mcp
Medium confidenceExposes Contentful webhooks and event history through MCP resources, allowing clients to query recent content changes, publish events, and understand content modification patterns. Implements event filtering and pagination for webhook history. Enables AI agents to react to content changes or audit modification trails.
Exposes Contentful's webhook history as queryable MCP resources, enabling LLMs to understand content change patterns and audit trails without requiring custom webhook handlers or event log storage
More accessible than raw webhook APIs because it provides query-based access to event history, and more actionable than webhook logs because MCP clients can filter and summarize events programmatically
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 @contentful/mcp-server, ranked by overlap. Discovered automatically through the match graph.
Contentful
** - Interact with your content on the Contentful platform
Kontent.ai
** - Create, manage, and explore your content and content model using natural language in any MCP-compatible AI tool.
webiny-js
Open-source, self-hosted CMS platform on AWS serverless (Lambda, DynamoDB, S3). TypeScript framework with multi-tenancy, lifecycle hooks, GraphQL API, and AI-assisted development via MCP server. Built for developers at large organizations.
@modelcontextprotocol/inspector-client
Client-side application for the Model Context Protocol inspector
@mcp-use/inspector
MCP Inspector - A tool for inspecting and debugging MCP servers
ifconfig-mcp
ModelContextProtocol starter server
Best For
- ✓teams using Claude or other MCP-compatible LLMs to manage Contentful content
- ✓developers building AI-powered content generation workflows
- ✓non-technical content managers who want to interact with Contentful via natural language
- ✓content teams automating entry creation workflows with AI assistance
- ✓developers building AI-powered content management systems
- ✓organizations wanting to delegate content updates to LLM agents with guardrails
- ✓teams building AI-powered content discovery and search features
- ✓developers creating conversational interfaces to Contentful data
Known Limitations
- ⚠read-only introspection of schema — does not modify content type definitions
- ⚠requires MCP client support (Claude Desktop, custom MCP hosts) — not usable via standard Contentful UI
- ⚠schema changes in Contentful may require server restart to reflect in MCP protocol
- ⚠requires Content Management API key with write permissions — higher security risk than read-only keys
- ⚠no built-in approval workflows or staging — entries are published immediately or saved as drafts based on configuration
- ⚠batch operations are sequential tool calls, not atomic transactions — partial failures possible
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
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Contentful MCP Server - Model Context Protocol server for Contentful
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