anyapi-mcp-server

A universal Model Context Protocol (MCP) server that connects any REST API to AI assistants like Claude, Cursor, and other LLM-powered tools — just point it at an OpenAPI spec or Postman collection.

Instead of building a custom MCP server for every API, anyapi-mcp-server reads your spec file and dynamically creates tools with GraphQL-style field selection and automatic schema inference.

Features

Works with any REST API — provide an OpenAPI (JSON/YAML) or Postman Collection v2.x spec
GraphQL-style queries — select only the fields you need from API responses
Automatic schema inference — calls an endpoint once, infers the response schema, then lets you query specific fields
Multi-sample merging — samples up to 10 array elements to build richer schemas that capture fields missing from individual items
Mutation support — POST/PUT/DELETE/PATCH endpoints with OpenAPI request body schemas get GraphQL mutation types with typed inputs
Smart query suggestions — call_api returns ready-to-use GraphQL queries based on the inferred schema
Response caching — 30-second TTL cache prevents duplicate HTTP calls across consecutive call_api → query_api flows
Retry with backoff — automatic retries with exponential backoff and jitter for 429/5xx errors, honoring Retry-After headers
Multi-format responses — parses JSON, XML, CSV, and plain text responses automatically
Built-in pagination — API-level pagination via params; client-side slicing with top-level limit/offset
Spec documentation lookup — explain_api returns rich endpoint docs (parameters, response codes, deprecation, request body schema) without making HTTP requests
Concurrent batch queries — batch_query fetches data from up to 10 endpoints in parallel, returning all results in one tool call
Per-request headers — override default headers on individual call_api/query_api/batch_query calls
Environment variable interpolation — use ${ENV_VAR} in base URLs and headers
Request logging — optional NDJSON request/response log with sensitive header masking

Installation

npm install -g anyapi-mcp-server

Required arguments

Flag	Description
`--name`	Server name (e.g. `petstore`)

Either one of

Flag	Description
`--spec`	Path to OpenAPI spec file (JSON or YAML) or Postman Collection
`--base-url`	API base URL (e.g. `https://api.example.com`). Supports `${ENV_VAR}` interpolation.

You can provide both --spec and --base-url together. If only --spec is given, the base URL is read from the spec. If only --base-url is given, endpoints are discovered dynamically.

Optional arguments

Flag	Description
`--header`	HTTP header as `"Key: Value"` (repeatable). Supports `${ENV_VAR}` interpolation in values.
`--log`	Path to request/response log file (NDJSON format). Sensitive headers are masked automatically.

Example: Cursor / Claude Desktop configuration

Add to your MCP configuration (e.g. ~/.cursor/mcp.json or Claude Desktop config):

Cloudflare API

{
  "mcpServers": {
    "cloudflare": {
      "command": "npx",
      "args": [
        "-y",
        "anyapi-mcp-server",
        "--name", "cloudflare",
        "--spec", "/path/to/cloudflare-openapi.json",
        "--base-url", "https://api.cloudflare.com/client/v4",
        "--header", "Authorization: Bearer ${CLOUDFLARE_API_TOKEN}"
      ],
      "env": {
        "CLOUDFLARE_API_TOKEN": "your-cloudflare-api-token"
      }
    }
  }
}

Datadog API

{
  "mcpServers": {
    "datadog": {
      "command": "npx",
      "args": [
        "-y",
        "anyapi-mcp-server",
        "--name", "datadog",
        "--spec", "/path/to/datadog-openapi.json",
        "--base-url", "https://api.datadoghq.com/api/v1",
        "--header", "DD-API-KEY: ${DD_API_KEY}",
        "--header", "DD-APPLICATION-KEY: ${DD_APP_KEY}"
      ],
      "env": {
        "DD_API_KEY": "your-datadog-api-key",
        "DD_APP_KEY": "your-datadog-app-key"
      }
    }
  }
}

Metabase API

{
  "mcpServers": {
    "metabase": {
      "command": "npx",
      "args": [
        "-y",
        "anyapi-mcp-server",
        "--name", "metabase",
        "--base-url", "https://your-metabase-instance.com/api",
        "--header", "x-api-key: ${METABASE_API_KEY}"
      ],
      "env": {
        "METABASE_API_KEY": "your-metabase-api-key"
      }
    }
  }
}

Tools

The server exposes five MCP tools:

`list_api`

Browse and search available API endpoints from the spec.

Call with no arguments to see all categories/tags
Provide category to list endpoints in a tag
Provide search to search across paths and descriptions
Results are paginated with limit (default 20) and offset

GraphQL selection for categories:

{
  items {
    tag
    endpointCount
  }
  _count
}

GraphQL selection for endpoints:

{
  items {
    method
    path
    summary
  }
  _count
}

`call_api`

Inspect an API endpoint by making a real request and returning the inferred GraphQL schema (SDL). No response data is returned — use query_api to fetch actual data.

Returns the full schema SDL showing all available fields and types
Returns accepted parameters (name, location, required) from the API spec
Returns suggestedQueries — ready-to-use GraphQL queries generated from the schema
Accepts optional headers to override defaults for this request
For write operations (POST/PUT/DELETE/PATCH) with request body schemas, the schema includes a Mutation type

`query_api`

Fetch data from an API endpoint, returning only the fields you select via GraphQL.

Object responses:

{
  id
  name
  collection {
    id
    name
  }
}

Array responses:

{
  items {
    id
    name
  }
  _count
}

Mutation syntax for writes:

mutation {
  post_endpoint(input: { ... }) {
    id
    name
  }
}

Supports limit and offset for client-side slicing of already-fetched data
For API-level pagination, pass limit/offset inside params instead
Accepts optional headers to override defaults for this request

`explain_api`

Get detailed documentation for an endpoint directly from the spec — no HTTP request is made.

Returns summary, description, operationId, deprecation status, tag
Lists all parameters with name, location (path/query/header), required flag, and description
Shows request body schema with property types, required fields, and descriptions
Lists response status codes with descriptions (e.g. 200 OK, 404 Not Found)
Includes external docs link when available

`batch_query`

Fetch data from multiple endpoints concurrently in a single tool call.

Accepts an array of 1–10 requests, each with method, path, params, body, query, and optional headers
All requests execute in parallel via Promise.allSettled — one failure does not affect the others
Each request follows the query_api flow: HTTP fetch → schema inference → GraphQL field selection
Returns an array of results: { method, path, data } on success or { method, path, error } on failure
Run call_api first on each endpoint to discover the schema field names

Workflow

Discover endpoints with list_api
Understand an endpoint with explain_api to see its parameters, request body, and response codes
Inspect a specific endpoint with call_api to see the inferred response schema and suggested queries
Query the endpoint with query_api to fetch exactly the fields you need
Batch multiple queries with batch_query when you need data from several endpoints at once

How It Works

OpenAPI/Postman spec
        │
        ▼
   ┌─────────┐  ┌─────────────┐  ┌──────────┐  ┌───────────┐  ┌─────────────┐
   │list_api │  │ explain_api │  │ call_api │  │ query_api │  │ batch_query │
   │(browse) │  │   (docs)    │  │ (schema) │  │  (data)   │  │ (parallel)  │
   └─────────┘  └─────────────┘  └──────────┘  └───────────┘  └─────────────┘
        │          │ no HTTP          │               │             │
        ▼          ▼ request          ▼               ▼             ▼
   Spec index   Spec index     REST API call    REST API call  N concurrent
   (tags,       (params,       (with retry      (cached if     REST API calls
    paths)       responses,     + caching)       same as        + GraphQL
                 body schema)       │            call_api)      execution
                                    ▼               │
                               Infer GraphQL        ▼
                               schema from     Execute GraphQL
                               JSON response   query against
                                               response data

The spec file is parsed at startup into an endpoint index with tags, paths, parameters, and request body schemas
call_api makes a real HTTP request, infers a GraphQL schema from the JSON response, and caches both the response (30s TTL) and the schema
query_api re-uses the cached response if called within 30s, executes your GraphQL field selection against the data, and returns only the fields you asked for
Write operations (POST/PUT/DELETE/PATCH) with OpenAPI request body schemas get a Mutation type with typed GraphQLInputObjectType inputs

Supported Spec Formats

OpenAPI 3.x (JSON or YAML)
OpenAPI 2.0 / Swagger (JSON or YAML)
Postman Collection v2.x (JSON)

$ref resolution is supported for OpenAPI request body schemas. Postman :param path variables are converted to OpenAPI-style {param} automatically.

License

Proprietary Non-Commercial. Free for personal and educational use. Commercial use requires written permission. See LICENSE for details.

anyapi-mcp-server