jitapi
Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.
README
JitAPI
Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically.
<!-- mcp-name: io.github.nk3750/jitapi -->
JitAPI is an MCP server that lets Claude interact with any API from its OpenAPI spec. Instead of dumping hundreds of endpoints into context, JitAPI uses semantic search and a dependency graph to surface only what's needed — then Claude plans and executes the calls.
https://github.com/user-attachments/assets/53f72f89-a41a-4a9c-a688-ec876ea05fbd
The Problem
Stripe has 300+ endpoints. GitHub has 800+. Loading the full spec into Claude's context wastes tokens and causes hallucinations. Writing a custom MCP server for every API you use doesn't scale.
JitAPI solves this: register any OpenAPI spec once, then ask for what you need in plain English. It finds the right endpoints, resolves dependencies between them, and lets Claude execute the calls.
Quick Start
pip install jitapi
Add to your Claude Code config (.mcp.json):
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": ["jitapi"]
}
}
}
That's it. No API keys required — JitAPI uses local embeddings out of the box.
Then in Claude:
You: Register the GitHub API from https://raw.githubusercontent.com/github/rest-api-description/main/descriptions/api.github.com/api.github.com.json
Claude: ✓ Registered GitHub v3 REST API — 1,107 endpoints indexed
You: List my repos
Claude: [searches for "list repositories for authenticated user" → finds GET /user/repos → executes]
Here are your repositories: ...
Multi-API Orchestration
The killer feature: register multiple APIs and ask questions that span them. JitAPI searches across all registered APIs and Claude chains the calls.
You: Register the TMDB API and OpenWeatherMap API
Claude: ✓ Registered both APIs
You: Find the top popular movie on TMDB, then get the weather where it was filmed
Claude: [searches TMDB → GET /movie/popular → GET /movie/{id} for production locations
→ searches OpenWeather → GET /data/2.5/weather with the city]
The #1 popular movie is "Inception", filmed in Los Angeles.
Current weather in LA: 72°F, partly cloudy.
How It Works
Register API Ask a question
│ │
▼ ▼
Parse OpenAPI spec Embed query → vector search
│ │
▼ ▼
Build dependency graph Find relevant endpoints
│ │
▼ ▼
Embed all endpoints Expand with dependencies
│ │
▼ ▼
Store in vector DB Return schemas → Claude executes
- Register — Parse an OpenAPI spec, build a dependency graph (which endpoints need data from which other endpoints), and create searchable embeddings for all endpoints
- Search — When you ask a question, JitAPI embeds your query and finds the most relevant endpoints via cosine similarity
- Expand — The dependency graph adds any prerequisite endpoints (e.g., "you need to call GET /users first to get the user_id for POST /orders")
- Execute — Claude gets the endpoint schemas and makes the API calls, passing data between steps
MCP Tools
| Tool | Description |
|---|---|
register_api |
Register an API from an OpenAPI spec URL |
list_apis |
List all registered APIs and their endpoint counts |
search_endpoints |
Semantic search across endpoints using natural language |
get_workflow |
Find relevant endpoints with dependency resolution and full schemas |
get_endpoint_schema |
Get the complete schema for a specific endpoint |
call_api |
Execute a single API call with auth, path params, query params, and body |
set_api_auth |
Configure authentication (API key, bearer token, basic auth) |
delete_api |
Remove a registered API and all its data |
Setup
Claude Code
Create .mcp.json in your project directory (or ~/.claude.json for global access):
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": ["jitapi"]
}
}
}
Claude Desktop
Add to your Claude Desktop config:
| OS | Config path |
|---|---|
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
| Windows | %APPDATA%\Claude\claude_desktop_config.json |
| Linux | ~/.config/Claude/claude_desktop_config.json |
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": ["jitapi"]
}
}
}
Embedding Providers
JitAPI works out of the box with local embeddings (fastembed) — no API keys needed. For better search quality on large APIs, you can add a cloud embedding provider:
| Provider | Quality | Setup |
|---|---|---|
| Local (default) | Good | Nothing — works immediately |
| Voyage AI (recommended) | Excellent | pip install jitapi[voyage] + set VOYAGE_API_KEY |
| OpenAI | Excellent | pip install jitapi[openai] + set OPENAI_API_KEY |
| Cohere | Very good | pip install jitapi[cohere] + set COHERE_API_KEY |
Set the API key in your MCP config's env block:
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": ["jitapi"],
"env": {
"VOYAGE_API_KEY": "your-key-here"
}
}
}
}
Provider is auto-detected from available environment variables. Priority: Voyage AI > OpenAI > Cohere > local.
Authentication
Configure API authentication after registering. The recommended approach uses environment variables so secrets are never written to disk:
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": ["jitapi"],
"env": {
"GITHUB_TOKEN": "ghp_...",
"OPENWEATHER_API_KEY": "your-key-here"
}
}
}
}
Then tell Claude to use the env var:
You: Set bearer auth for GitHub using env var GITHUB_TOKEN
Claude: [calls set_api_auth with auth_type="bearer", env_var="GITHUB_TOKEN"]
✓ Auth configured for github (from env var $GITHUB_TOKEN)
With env_var, JitAPI reads the secret from the environment at request time — only the env var name is persisted, never the credential itself.
You can also pass credentials directly (they'll be stored in ~/.jitapi/auth.json with 0600 permissions):
You: Set API key auth for OpenWeather with param name "appid"
Claude: [calls set_api_auth with auth_type="api_key_query", credential="...", param_name="appid"]
✓ Auth configured for openweather
Supported auth types: bearer, api_key_header, api_key_query, basic.
Security note: When using
env_var, credentials are resolved at runtime and never touch the filesystem. When passingcredentialdirectly, secrets are stored as plaintext JSON at~/.jitapi/auth.json(file permissions0600, directory0700). For production use, prefer theenv_varapproach.
Environment Variables
| Variable | Required | Description |
|---|---|---|
VOYAGE_API_KEY |
No | Voyage AI API key (recommended cloud provider) |
OPENAI_API_KEY |
No | OpenAI API key (alternative cloud provider) |
COHERE_API_KEY |
No | Cohere API key (alternative cloud provider) |
JITAPI_STORAGE_DIR |
No | Data directory (default: ~/.jitapi) |
JITAPI_LOG_LEVEL |
No | DEBUG, INFO, WARNING, ERROR (default: INFO) |
Development
git clone https://github.com/nk3750/jitapi.git
cd jitapi
pip install -e ".[dev]"
pytest
ruff check src/
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.