What can @cap-js/mcp-server do?

cap project structure introspection and schema extraction, mcp resource and tool registration for cap development, ai-assisted cds entity and service code generation, cds syntax validation and error reporting, project-aware context management for llm interactions, service endpoint discovery and documentation generation, multi-provider llm integration via mcp, database query and odata request generation

@cap-js/mcp-server

MCP ServerFree

Model Context Protocol (MCP) server for AI-assisted development of CAP applications.

Open Source

/ 100

8 capabilities

Capabilities8 decomposed

cap project structure introspection and schema extraction

Medium confidence

Analyzes CAP (Cloud Application Programming) project structure to extract data models, service definitions, and configuration metadata. Implements filesystem-based AST parsing of CDS (Core Data Services) files to build a semantic representation of the application architecture, enabling AI models to understand domain entities, relationships, and service boundaries without manual documentation.

Solves for

I want Claude or another AI to understand my CAP project structure so it can generate code that follows my existing patternsI need to expose my data model and service definitions to an LLM so it can suggest database queries or API endpointsI want an AI to analyze my CDS files and recommend schema improvements or identify unused entities

Best for

SAP CAP developers using AI-assisted development workflows

Teams building enterprise applications on CAP who want LLM-aware code generation

Organizations migrating legacy SAP systems and need AI to understand domain models

Requires

Node.js 16+

CAP project with valid cds files in db/, srv/, or app/ directories

MCP client (Claude Desktop, Cline, or compatible tool) to consume the server

Limitations

Limited to CDS syntax — does not parse custom JavaScript service implementations or business logic

Schema extraction is static — does not reflect runtime state or dynamic entity modifications

No support for external data sources or OData metadata beyond CAP's native definitions

What makes it unique

Purpose-built for SAP CAP ecosystem — parses CDS syntax natively and maps to CAP's specific service and entity model, rather than generic code analysis. Integrates directly with CAP's configuration system to understand project layout conventions.

vs alternatives

Unlike generic code indexing tools, this MCP server understands CAP-specific patterns (aspects, compositions, service definitions) and can expose them to LLMs in a semantically meaningful way for domain-aware code generation.

mcp resource and tool registration for cap development

Medium confidence

Implements the Model Context Protocol (MCP) server specification to register CAP-specific resources (data models, services, configurations) and tools (code generators, validators, query builders) as callable functions within AI client contexts. Uses MCP's resource URI scheme and tool JSON-Schema definitions to create a standardized interface that allows Claude and other MCP-compatible clients to discover and invoke CAP development capabilities.

Solves for

I want my AI assistant to have access to CAP-specific tools like entity validators or query generators without leaving the chat interfaceI need to expose my project's schema as a queryable resource so the AI can reference it in code suggestionsI want to register custom CAP development tools (migrations, deployment helpers) as MCP tools that Claude can call

Best for

AI-assisted development teams using Claude Desktop or Cline with MCP support

CAP developers who want to extend their AI assistant with domain-specific tools

Organizations building custom LLM workflows around CAP development

Requires

Node.js 16+

MCP client with server support (Claude Desktop 0.1.0+, Cline, or equivalent)

CAP project initialized with @cap-js/mcp-server package installed

Limitations

Requires MCP-compatible client — does not work with standard REST APIs or non-MCP LLM interfaces

Tool execution runs in the MCP server process — no built-in sandboxing or resource limits

Schema-based tool definitions may not capture complex validation logic or side effects

What makes it unique

Implements MCP server specification for CAP domain — defines CAP-specific resource types (entities, services, configurations) and tool schemas that map to CAP development workflows, rather than generic tool registration.

vs alternatives

Tighter integration with CAP than generic MCP servers — understands CAP's service model, entity relationships, and development patterns, allowing more intelligent tool suggestions and resource navigation.

ai-assisted cds entity and service code generation

Medium confidence

Generates CDS entity definitions, service implementations, and configuration boilerplate based on natural language descriptions or schema templates. Uses LLM context (via MCP) to understand existing project patterns and generates code that follows the project's conventions, naming standards, and architectural patterns. Integrates with the project's schema introspection to ensure generated code is compatible with existing entities and services.

Solves for

I want to describe a new entity in natural language and have the AI generate the CDS definition with proper associations and annotationsI need to create a new service endpoint that exposes existing entities — I want the AI to generate the service.js file following my project's patternsI want to generate database migration scripts or seed data based on my data model

Best for

CAP developers accelerating entity and service scaffolding

Teams with consistent coding standards who want AI to maintain those patterns

Rapid prototyping scenarios where developers want to iterate on schema quickly

Requires

Node.js 16+

CAP project with existing db/ and srv/ directories

MCP client with code generation support (Claude with extended context)

Limitations

Generated code may require manual review for complex business logic or validations

Does not automatically generate tests or documentation

Limited to CDS syntax — cannot generate custom JavaScript service implementations with complex logic

What makes it unique

Leverages project-specific schema introspection to generate code that respects existing naming conventions, association patterns, and service structure — not generic boilerplate, but context-aware generation.

vs alternatives

Unlike generic code generators, this capability understands CAP's CDS syntax and can generate code that integrates seamlessly with existing entities and services by analyzing the project's actual structure.

cds syntax validation and error reporting

Medium confidence

Validates CDS file syntax and semantic correctness (entity definitions, associations, service definitions, annotations) and reports errors with precise line numbers and remediation suggestions. Implements a CDS parser that checks for common mistakes (circular associations, undefined entity references, invalid annotations) and provides actionable error messages that can be displayed in the AI client or IDE.

Solves for

I want the AI to catch syntax errors in my CDS files before I deployI need validation feedback on my entity associations to ensure they're correctly definedI want the AI to warn me about deprecated CDS patterns or anti-patterns in my schema

Best for

CAP developers using AI-assisted development who want real-time validation feedback

Teams implementing linting and validation in their CI/CD pipelines

Organizations building custom CAP development tools that need validation capabilities

Requires

Node.js 16+

CDS files in valid UTF-8 encoding

CAP project with cds configuration

Limitations

Validates CDS syntax only — does not validate JavaScript service implementations

Does not perform runtime validation or type checking

Limited to CAP's CDS specification — does not support custom extensions or dialects

What makes it unique

CDS-specific validator that understands CAP's entity model, association rules, and annotation semantics — not a generic syntax checker, but domain-aware validation.

vs alternatives

Provides CAP-specific error messages and suggestions (e.g., 'Association must reference a valid entity' with the actual entity name) rather than generic parser errors.

project-aware context management for llm interactions

Medium confidence

Maintains and exposes project context (schema, services, configurations, recent files) to the LLM through MCP resources, enabling the AI to make informed suggestions without requiring developers to manually paste code snippets. Implements a context indexing system that tracks project structure changes and updates the available resources dynamically, allowing the LLM to reference current project state in its responses.

Solves for

I want the AI to know about my existing entities and services so it can suggest compatible code without me having to describe themI need the AI to understand my project's naming conventions and architectural patterns so it generates code that fitsI want the AI to have access to my project's configuration so it can suggest environment-specific code

Best for

CAP development teams using AI assistants for code generation and suggestions

Developers who want AI to maintain consistency with existing project patterns

Organizations with large CAP projects where manual context passing is impractical

Requires

Node.js 16+

CAP project with initialized cds configuration

MCP client with resource support

Limitations

Context is read-only from the MCP server perspective — does not automatically update when files change on disk

Large projects may have slow context indexing on first load

Context size is limited by MCP client's context window — very large schemas may be truncated

What makes it unique

Implements project-aware context indexing specific to CAP structure — understands db/, srv/, and app/ directory conventions and exposes them as queryable MCP resources rather than requiring manual context assembly.

vs alternatives

Automatically maintains project context without developer intervention, unlike manual context passing or generic code indexing tools that don't understand CAP's specific directory and file conventions.

service endpoint discovery and documentation generation

Medium confidence

Analyzes CAP service definitions to discover exposed endpoints, their request/response schemas, and authentication requirements. Generates documentation (OpenAPI/Swagger-compatible format or markdown) that describes available services, entities, and operations, making it easy for AI assistants to understand and suggest correct API usage patterns.

Solves for

I want the AI to know what endpoints my CAP services expose so it can suggest correct API callsI need to generate API documentation for my CAP services automaticallyI want the AI to understand my service's request/response schemas so it can validate generated code

Best for

CAP developers building APIs who want AI-assisted client code generation

Teams that need to keep API documentation in sync with code

Organizations building internal tools that consume CAP services

Requires

Node.js 16+

CAP services defined in CDS files

Service definitions with entity references

Limitations

Discovers endpoints from CDS definitions only — does not analyze runtime behavior or custom middleware

Does not automatically detect authentication schemes beyond CAP's standard annotations

Generated documentation may need manual refinement for complex business logic

What makes it unique

Extracts endpoint definitions from CAP's CDS service syntax and generates documentation that reflects CAP's specific service model (entity exposure, CRUD operations, custom actions) rather than generic API analysis.

vs alternatives

Understands CAP's service definition patterns and can generate accurate endpoint documentation without requiring manual OpenAPI specifications or external API documentation tools.

multi-provider llm integration via mcp

Medium confidence

Provides a standardized MCP interface that allows any MCP-compatible LLM client (Claude, Cline, custom agents) to interact with CAP development tools and project context. Abstracts away provider-specific details and uses MCP's protocol to ensure compatibility across different AI platforms and clients without requiring provider-specific SDKs or integrations.

Solves for

I want to use Claude, Cline, or another AI tool with my CAP project without building custom integrationsI need my CAP development tools to work with multiple AI assistants and clientsI want to build custom LLM agents that can interact with my CAP project using a standard protocol

Best for

Teams using multiple AI assistants and wanting consistent CAP integration across all of them

Organizations building custom LLM agents that need CAP development capabilities

Developers who want to avoid vendor lock-in to a single AI provider

Requires

Node.js 16+

MCP-compatible client (Claude Desktop 0.1.0+, Cline, or custom implementation)

@cap-js/mcp-server package installed and running

Limitations

Limited to MCP-compatible clients — does not work with REST-only or proprietary AI platforms

MCP protocol overhead adds latency compared to direct API calls

Feature parity depends on MCP client's implementation of the protocol

What makes it unique

Implements MCP as a protocol abstraction layer for CAP development — allows any MCP-compatible client to access CAP tools without provider-specific code, enabling true interoperability.

vs alternatives

Unlike provider-specific integrations (e.g., Claude plugins, Copilot extensions), MCP provides a vendor-neutral protocol that works across multiple AI platforms and clients.

database query and odata request generation

Medium confidence

Generates CDS Query Language (CQL) queries and OData requests based on natural language descriptions or schema context. Understands entity relationships, filters, projections, and aggregations, and generates syntactically correct queries that can be executed against CAP's data layer. Validates generated queries against the project's schema to ensure they reference valid entities and properties.

Solves for

I want the AI to generate a CQL query that filters entities by specific criteriaI need to create an OData request that joins multiple entities and applies filtersI want the AI to suggest efficient queries based on my data model and available indexes

Best for

CAP developers building data-driven features who want AI-assisted query generation

Teams implementing complex data retrieval logic and wanting to avoid manual query writing

Rapid development scenarios where query generation accelerates feature implementation

Requires

Node.js 16+

CAP project with defined entities and data model

Understanding of CQL or OData syntax (for validation)

Limitations

Generated queries may not be optimal for performance — does not consider indexes or query plans

Limited to CQL and OData syntax — does not generate raw SQL or database-specific queries

Does not automatically handle complex business logic or custom query handlers

What makes it unique

Generates queries that respect CAP's entity model and CQL syntax — understands associations, compositions, and CAP-specific query semantics rather than generic SQL generation.

vs alternatives

Produces CAP-native queries (CQL/OData) that integrate seamlessly with CAP's data layer, unlike generic SQL generators that would require translation or custom adapters.

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 @cap-js/mcp-server, ranked by overlap. Discovered automatically through the match graph.

MCP Server32

@cap-js/mcp-server

Model Context Protocol (MCP) server for AI-assisted development of CAP applications.

cap application context exposure via mcp protocoltool calling interface for cap development taskscds entity and service schema introspectioncap-aware code generation with template support

4 shared capabilities

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@coinbase/cds-mcp-server

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mcp-tool-registry-for-design-componentscomponent-metadata-extraction-and-schema-generation

2 shared capabilities

MCP Server32

@theia/ai-mcp

Theia - MCP Integration

mcp capability discovery and schema introspection

1 shared capability

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AllInOneMCP

MCP of MCPs. A central hub for MCP servers. Helps you discover available MCP servers and learn how to install and use them. REMOTE! Use the url [https://mcp.pfvc.io/mcp/](https://mcp.pfvc.io/mcp/) to add the server. **Remember the final backslash\*\*.

mcp server capability schema extraction and documentation

1 shared capability

MCP Server27

decocms

Deco CMS — Self-hostable MCP Gateway for managing AI connections and tools

tool discovery and capability introspection

1 shared capability

MCP Server20

@mcp-contracts/cli

CLI tool for capturing and diffing MCP tool schemas

mcp tool schema capture and serialization

1 shared capability

Best For

✓SAP CAP developers using AI-assisted development workflows
✓Teams building enterprise applications on CAP who want LLM-aware code generation
✓Organizations migrating legacy SAP systems and need AI to understand domain models
✓AI-assisted development teams using Claude Desktop or Cline with MCP support
✓CAP developers who want to extend their AI assistant with domain-specific tools
✓Organizations building custom LLM workflows around CAP development
✓CAP developers accelerating entity and service scaffolding
✓Teams with consistent coding standards who want AI to maintain those patterns

Known Limitations

⚠Limited to CDS syntax — does not parse custom JavaScript service implementations or business logic
⚠Schema extraction is static — does not reflect runtime state or dynamic entity modifications
⚠No support for external data sources or OData metadata beyond CAP's native definitions
⚠Requires MCP-compatible client — does not work with standard REST APIs or non-MCP LLM interfaces
⚠Tool execution runs in the MCP server process — no built-in sandboxing or resource limits
⚠Schema-based tool definitions may not capture complex validation logic or side effects

Requirements

Node.js 16+CAP project with valid cds files in db/, srv/, or app/ directoriesMCP client (Claude Desktop, Cline, or compatible tool) to consume the serverMCP client with server support (Claude Desktop 0.1.0+, Cline, or equivalent)CAP project initialized with @cap-js/mcp-server package installedCAP project with existing db/ and srv/ directoriesMCP client with code generation support (Claude with extended context)CDS files in valid UTF-8 encoding

Input / Output

Accepts: CDS data model files (.cds), Service definition files (.cds), Configuration files (package.json, .cdsrc.json), MCP resource URIs (cap://schema/entities, cap://services), Tool invocation payloads with JSON arguments, natural language entity descriptions, existing CDS schema (for pattern matching), service endpoint specifications, CDS file content (text), CDS file paths, CAP project directory, CDS files, package.json and configuration files, CDS service definitions, Entity schemas, MCP protocol messages, resource requests, tool invocations, natural language query descriptions, entity schema definitions, filter and projection specifications

Produces: structured JSON schema representation, entity relationship diagrams (text-based), service endpoint documentation, MCP resource content (JSON, text), Tool execution results (structured data, code, validation reports), CDS entity definition files, CDS service definition files, JavaScript service implementation stubs, validation error objects with line/column numbers, remediation suggestions (text), severity levels (error, warning, info), MCP resource URIs for schema, services, configurations, JSON representations of project structure, context summaries for LLM consumption, OpenAPI/Swagger JSON, Markdown documentation, endpoint metadata (methods, paths, parameters), MCP protocol responses, resource content, tool execution results, CQL query strings, OData request URLs, query metadata (entities, filters, projections)

UnfragileRank

Adoption48%(30% weight)

Quality17%(25% weight)

Ecosystem40%(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

8 capabilities

Visit @cap-js/mcp-server→

Repository Details

Package Details

npm

Registry

0.0.4

Version

13,055

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Model Context Protocol (MCP) server for AI-assisted development of CAP applications.

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Capabilities8 decomposed

cap project structure introspection and schema extraction

Medium confidence

Solves for

Best for

SAP CAP developers using AI-assisted development workflows

Teams building enterprise applications on CAP who want LLM-aware code generation

Organizations migrating legacy SAP systems and need AI to understand domain models

Requires

Node.js 16+

CAP project with valid cds files in db/, srv/, or app/ directories

MCP client (Claude Desktop, Cline, or compatible tool) to consume the server

Limitations

Limited to CDS syntax — does not parse custom JavaScript service implementations or business logic

Schema extraction is static — does not reflect runtime state or dynamic entity modifications

No support for external data sources or OData metadata beyond CAP's native definitions

What makes it unique

vs alternatives

mcp resource and tool registration for cap development

Medium confidence

Solves for

Best for

AI-assisted development teams using Claude Desktop or Cline with MCP support

CAP developers who want to extend their AI assistant with domain-specific tools

Organizations building custom LLM workflows around CAP development

Requires

Node.js 16+

MCP client with server support (Claude Desktop 0.1.0+, Cline, or equivalent)

CAP project initialized with @cap-js/mcp-server package installed

Limitations

Requires MCP-compatible client — does not work with standard REST APIs or non-MCP LLM interfaces

Tool execution runs in the MCP server process — no built-in sandboxing or resource limits

Schema-based tool definitions may not capture complex validation logic or side effects

What makes it unique

vs alternatives

ai-assisted cds entity and service code generation

Medium confidence

Solves for

Best for

CAP developers accelerating entity and service scaffolding

Teams with consistent coding standards who want AI to maintain those patterns

Rapid prototyping scenarios where developers want to iterate on schema quickly

Requires

Node.js 16+

CAP project with existing db/ and srv/ directories

MCP client with code generation support (Claude with extended context)

Limitations

Generated code may require manual review for complex business logic or validations

Does not automatically generate tests or documentation

Limited to CDS syntax — cannot generate custom JavaScript service implementations with complex logic

What makes it unique

vs alternatives

cds syntax validation and error reporting

Medium confidence

Solves for

Best for

CAP developers using AI-assisted development who want real-time validation feedback

Teams implementing linting and validation in their CI/CD pipelines

Organizations building custom CAP development tools that need validation capabilities

Requires

Node.js 16+

CDS files in valid UTF-8 encoding

CAP project with cds configuration

Limitations

Validates CDS syntax only — does not validate JavaScript service implementations

Does not perform runtime validation or type checking

Limited to CAP's CDS specification — does not support custom extensions or dialects

What makes it unique

CDS-specific validator that understands CAP's entity model, association rules, and annotation semantics — not a generic syntax checker, but domain-aware validation.

vs alternatives

Provides CAP-specific error messages and suggestions (e.g., 'Association must reference a valid entity' with the actual entity name) rather than generic parser errors.

project-aware context management for llm interactions

Medium confidence

Solves for

Best for

CAP development teams using AI assistants for code generation and suggestions

Developers who want AI to maintain consistency with existing project patterns

Organizations with large CAP projects where manual context passing is impractical

Requires

Node.js 16+

CAP project with initialized cds configuration

MCP client with resource support

Limitations

Context is read-only from the MCP server perspective — does not automatically update when files change on disk

Large projects may have slow context indexing on first load

Context size is limited by MCP client's context window — very large schemas may be truncated

What makes it unique

vs alternatives

service endpoint discovery and documentation generation

Medium confidence

Solves for

Best for

CAP developers building APIs who want AI-assisted client code generation

Teams that need to keep API documentation in sync with code

Organizations building internal tools that consume CAP services

Requires

Node.js 16+

CAP services defined in CDS files

Service definitions with entity references

Limitations

Discovers endpoints from CDS definitions only — does not analyze runtime behavior or custom middleware

Does not automatically detect authentication schemes beyond CAP's standard annotations

Generated documentation may need manual refinement for complex business logic

What makes it unique

vs alternatives

Understands CAP's service definition patterns and can generate accurate endpoint documentation without requiring manual OpenAPI specifications or external API documentation tools.

multi-provider llm integration via mcp

Medium confidence

Solves for

Best for

Teams using multiple AI assistants and wanting consistent CAP integration across all of them

Organizations building custom LLM agents that need CAP development capabilities

Developers who want to avoid vendor lock-in to a single AI provider

Requires

Node.js 16+

MCP-compatible client (Claude Desktop 0.1.0+, Cline, or custom implementation)

@cap-js/mcp-server package installed and running

Limitations

Limited to MCP-compatible clients — does not work with REST-only or proprietary AI platforms

MCP protocol overhead adds latency compared to direct API calls

Feature parity depends on MCP client's implementation of the protocol

What makes it unique

Implements MCP as a protocol abstraction layer for CAP development — allows any MCP-compatible client to access CAP tools without provider-specific code, enabling true interoperability.

vs alternatives

Unlike provider-specific integrations (e.g., Claude plugins, Copilot extensions), MCP provides a vendor-neutral protocol that works across multiple AI platforms and clients.

database query and odata request generation

Medium confidence

Solves for

Best for

CAP developers building data-driven features who want AI-assisted query generation

Teams implementing complex data retrieval logic and wanting to avoid manual query writing

Rapid development scenarios where query generation accelerates feature implementation

Requires

Node.js 16+

CAP project with defined entities and data model

Understanding of CQL or OData syntax (for validation)

Limitations

Generated queries may not be optimal for performance — does not consider indexes or query plans

Limited to CQL and OData syntax — does not generate raw SQL or database-specific queries

Does not automatically handle complex business logic or custom query handlers

What makes it unique

Generates queries that respect CAP's entity model and CQL syntax — understands associations, compositions, and CAP-specific query semantics rather than generic SQL generation.

vs alternatives

Produces CAP-native queries (CQL/OData) that integrate seamlessly with CAP's data layer, unlike generic SQL generators that would require translation or custom adapters.

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

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@cap-js/mcp-server

Capabilities8 decomposed

cap project structure introspection and schema extraction

mcp resource and tool registration for cap development

ai-assisted cds entity and service code generation

cds syntax validation and error reporting

project-aware context management for llm interactions

service endpoint discovery and documentation generation

multi-provider llm integration via mcp

database query and odata request generation

Related Artifactssharing capabilities

@cap-js/mcp-server

@coinbase/cds-mcp-server

@theia/ai-mcp

AllInOneMCP

decocms

@mcp-contracts/cli

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

Package Details

About

Categories

Alternatives to @cap-js/mcp-server

Are you the builder of @cap-js/mcp-server?

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@cap-js/mcp-server

Capabilities8 decomposed

cap project structure introspection and schema extraction

mcp resource and tool registration for cap development

ai-assisted cds entity and service code generation

cds syntax validation and error reporting

project-aware context management for llm interactions

service endpoint discovery and documentation generation

multi-provider llm integration via mcp

database query and odata request generation

Related Artifactssharing capabilities

@cap-js/mcp-server

@coinbase/cds-mcp-server

@theia/ai-mcp

AllInOneMCP

decocms

@mcp-contracts/cli

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

Package Details

About

Categories

Alternatives to @cap-js/mcp-server

Are you the builder of @cap-js/mcp-server?

Get the weekly brief

Data Sources