api-mind
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@api-mind list available APIs"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
api-mind MCP Server
MCP server for API discovery from .mind spec files. Works with Claude Code, Claude Desktop, and any MCP-compatible AI assistant.
Quick Start
# 1. Install spec-mind to generate .mind files from OpenAPI specs
brew install spec-mind
# 2. Run the setup script from your project directory
curl -fsSL https://raw.githubusercontent.com/msegoviadev/api-mind-mcp/main/setup-mcp.sh | bash
# 3. Add your OpenAPI specs and generate .mind files
mkdir specs
cp your-api.yaml specs/
spec-mind sync --no-notation ./specs/
# 4. Restart Claude CodeIn Claude Code:
What APIs are available?
Show me the endpoints for payments
Call GET /payments/{id} in devRelated MCP server: apifable
Installation
Prerequisites
Install spec-mind to generate .mind files from your OpenAPI specs:
brew install spec-mindSetup
Run setup-mcp.sh from your project directory:
curl -fsSL https://raw.githubusercontent.com/msegoviadev/api-mind-mcp/main/setup-mcp.sh | bashOr for user-wide installation (all projects):
curl -fsSL https://raw.githubusercontent.com/msegoviadev/api-mind-mcp/main/setup-mcp.sh | bash -s -- --globalThe script:
Creates a
specs/directory in your projectRegisters api-mind in Claude Code with the correct specs path
Scaffolds
~/.config/api-mind/dev.envfor environment defaults
Usage
1. Add your API specs
# Copy your OpenAPI/Swagger YAML/JSON files to specs/
cp your-api.yaml specs/2. Generate .mind files
spec-mind sync --no-notation ./specs/3. Use in Claude Code
User: "What APIs are available?"
Claude: *uses list_apis tool*
"Found 2 APIs: ecommerce, payments"
User: "Show me payment endpoints"
Claude: *uses list_endpoints tool*
"POST /payments [auth: oauth2]
GET /payments/{id}"
User: "Call GET /payments/{id} in dev"
Claude: *uses get_endpoint_schema + get_call_context tools*
"Resolved base URL: https://api.dev.example.com
Calling GET /payments/123..."Tools
list_apis
Lists all APIs loaded from the specs folder.
Input: none
Output: JSON with API names, titles, base URLs, and environmentslist_endpoints
Lists endpoints across all APIs.
Input:
filter (optional): Substring match on method, path, or section
Output: JSON with environments and endpoint listget_endpoint_schema
Returns full context for an endpoint.
Input:
api: API name
method: HTTP method
path: Endpoint path
Output: Text block with base URL, environments, auth, and schemaCall before constructing curl to understand the endpoint contract.
get_call_context
Returns runtime context needed to execute API calls.
Input:
api: API name
env (optional): Environment to use (dev, stage, uat). Defaults to dev.
Output: Resolved base URL, active environment, and default values for credentials and parametersCall this before constructing curl when the user wants to actually invoke an endpoint.
Reads from ~/.config/api-mind/<env>.env and ~/.config/api-mind/<api>/<env>.env.
Auth Patterns
When get_endpoint_schema shows auth requirements, construct headers:
Auth in Schema | curl Header |
| No header |
|
|
|
|
|
|
|
|
Environment Defaults
get_call_context reads default values from ~/.config/api-mind/:
~/.config/api-mind/
dev.env # base defaults for all APIs (dev environment)
stage.env # base defaults for stage
auth0/
dev.env # API-specific overrides for auth0Each .env file uses key=value format (lines starting with # are ignored). The base_url key overrides the placeholder URL from the spec.
Example ~/.config/api-mind/dev.env:
base_url=https://api.dev.example.com
auth0_client_id=abc123
auth0_cacert=/etc/ssl/cert.pemsetup-mcp.sh scaffolds this file on first run.
Workflow
list_apis → list_endpoints → get_endpoint_schema → get_call_context → [LLM constructs curl] → bashlist_apis- Discover available APIslist_endpoints- Find relevant endpointsget_endpoint_schema- Get endpoint contract (URL, auth, schema)get_call_context- Resolve base URL and credentials for the target environmentLLM constructs curl command using resolved values
LLM executes via
bashtool
Advanced Configuration
Manual Installation
claude mcp add --transport stdio api-mind \
--env SPECS_DIR=/absolute/path/to/specs \
-- npx -y @msegoviadev/api-mind-mcpImportant: Always use absolute paths. MCP servers run as standalone processes without project context.
Project Configuration (.mcp.json)
Create .mcp.json in your project root:
{
"mcpServers": {
"api-mind": {
"command": "npx",
"args": ["-y", "@msegoviadev/api-mind-mcp"],
"env": {
"SPECS_DIR": "/absolute/path/to/specs"
}
}
}
}Note: Each team member needs their own .mcp.json with their absolute path. Add .mcp.json to .gitignore.
Development (Contributors)
git clone https://github.com/msegoviadev/api-mind-mcp
cd api-mind-mcp
npm install
npm run build
# Test locally
node dist/index.js /path/to/specsRelated
License
MIT
Available Tools
4 toolsget_call_contextA
Returns the runtime context needed to execute API calls: resolved base URL, active environment, and default values for credentials and parameters.
Call this before constructing a curl command when the user wants to actually invoke an endpoint. Do NOT call this just to browse or understand the API shape — use list_endpoints and get_endpoint_schema for that.
Reads from ~/.config/api-mind/.env and ~/.config/api-mind//.env. Defaults to "dev" unless the user specifies otherwise.
Inputs: api (required), env.
get_endpoint_schemaA
Returns the full context for a specific endpoint including resolved URL, auth requirements, and schema.
Use this to understand an endpoint before constructing a curl command to execute via the bash tool. Call this after list_endpoints to get the endpoint contract.
Auth Patterns
Auth in Schema | curl Header |
| No header |
|
|
|
|
|
|
|
|
NOTATION Legend
? optional | [ro] readOnly | [w] writeOnly | =val default
^ header | ~ cookie | *N multipleOf N | | enum or nullable
OneOf<A,B> on field = discriminated union
{*:T} = map/dict | {...} = open object | extends = allOf
& = inline extension | ~~name~~ deprecated | # = inline note
[multipart] [form] [binary] [text] = request body encoding
Inputs: api (required), path (required), method (required).
list_apisA
Lists all APIs loaded from the specs folder, with their names, titles, base URLs, and available environments.
Use this when you need to know what APIs are loaded or what environments a specific API supports. Call this first when the user references an API you haven't seen yet.
Inputs: no named parameters.
list_endpointsA
Lists all available endpoints across all loaded .mind files. Also surfaces the available environment names.
Use this to discover what endpoints exist across all APIs. Filter by method, path, or section. Call this when the user references an API or asks what's available.
Inputs: filter.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool has a distinct purpose: list_apis for API overview, list_endpoints for endpoint discovery, get_endpoint_schema for endpoint contract details, and get_call_context for runtime execution details. The descriptions explicitly clarify when to use each, preventing overlap.
All tool names follow a consistent verb_noun pattern (list_* and get_*), with verbs clearly indicating read-only discovery actions. The naming is predictable and uniform.
Four tools is well-scoped for a server focused on API discovery and context provision. Each tool covers a necessary step in the workflow from discovering APIs to preparing API calls, without redundancy.
The tool surface covers the full lifecycle of API exploration: discovering APIs, discovering endpoints, understanding schema/auth, and obtaining runtime context for actual calls. There are no obvious gaps for the server's stated purpose.
Maintenance
Related MCP Connectors
MCP server for AI access to Swagger by SmartBear.
Discover and call 10,000+ production APIs from one MCP server. Pay-per-call billing for AI agents.
MCP server that lets AI assistants use all OneSchema features exposed via the public API.
Hosted MCP server for live public-data APIs and Skills for AI agents.
Related MCP Servers
- AlicenseAqualityDmaintenanceA generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.211 npmMIT
- AlicenseAqualityBmaintenanceMCP server that helps AI agents explore OpenAPI specs, search endpoints, and generate TypeScript types.755 npm10MIT
- AlicenseNot gradedqualityBmaintenanceAn MCP server for API discovery and execution with a token-efficient search -> execute workflow over OpenAPI, Google Discovery, and optional native GraphQL and gRPC sources.127 npm13Apache 2.0
- AlicenseNot gradedqualityDmaintenanceAn MCP server that enables AI agents to explore, search, and query API definitions from OpenAPI/Swagger JSON files.23 npmMIT