JitAPI MCP server
Mengonversi spesifikasi OpenAPI menjadi interface agent yang dapat dieksekusi menggunakan semantic search dan dependency graph untuk mengotomatisasi pemanggilan API.
Juga dikenal sebagai nk3750/jitapi
- Stars
- 7
- Tools
- 8
- Unduhan, 30 hari
- 75
- Versi terbaru
- 0.1.1
- Commit terakhir
- 14 Jun 2026
- Lisensi
- MIT
Apa itu JitAPI MCP?
JitAPI adalah MCP server. Mengonversi spesifikasi OpenAPI menjadi interface agent yang dapat dieksekusi menggunakan semantic search dan dependency graph untuk mengotomatisasi pemanggilan API. Server ini menyediakan 8 tool, seperti register_api, list_apis, search_endpoints.
Ringkasan dibuat dari README proyek
Tentang JitAPI MCP server
JitAPI memungkinkan Anda menghubungkan Claude ke API yang kompleks hanya dengan menyediakan spesifikasi OpenAPI. Alih-alih membebani AI client dengan ratusan endpoint yang membuang-buang token, MCP server ini menggunakan semantic search dan dependency graph untuk mengidentifikasi tool yang hanya diperlukan untuk tugas tertentu. Server ini bekerja secara lokal melalui command line atau melalui Claude Desktop dengan mendaftarkan URL API dan membiarkan agent merencanakan serta mengeksekusi pemanggilan API tersebut.
Developer dapat mengelola beberapa API secara bersamaan untuk melakukan tugas orkestrasi yang melibatkan berbagai layanan. Sistem ini menggunakan local embeddings secara default, sehingga tidak memerlukan API key eksternal untuk operasi dasar, meskipun pengguna dapat memilih menggunakan Voyage AI, OpenAI, atau Cohere untuk kualitas pencarian yang lebih tinggi. Autentikasi ditangani melalui bearer tokens, custom headers, atau query parameters, dengan fokus pada keamanan melalui penggunaan environment variables agar kredensial tidak tersimpan di dalam disk.
Tool utama meliputi register_api untuk menambahkan spesifikasi baru, search_endpoints untuk penemuan menggunakan bahasa natural, dan call_api untuk mengeksekusi request yang sebenarnya. Server ini membangun dependency graph untuk memastikan bahwa jika satu endpoint memerlukan data dari endpoint lain, agent akan memahami urutan pemanggilan yang diperlukan.
Apa yang bisa Anda lakukan dengannya
- 1Otomatisasi workflow multi-APIMinta AI untuk mencari informasi dari satu layanan dan menggunakannya untuk melakukan query ke layanan kedua.
- 2Mengurangi penggunaan context windowHindari mengirim dokumentasi API yang masif ke AI dengan hanya menampilkan endpoint yang relevan.
- 3Menangani dependency API yang kompleksMemastikan agent mengetahui bahwa ia harus memanggil endpoint tertentu untuk mengambil ID sebelum memanggil endpoint berikutnya.
- 4Mengelola kredensial API secara amanKonfigurasi autentikasi untuk berbagai layanan menggunakan environment variables untuk mencegah rahasia tersimpan di filesystem.
Ditulis berdasarkan README proyek. Setiap use case diperiksa terhadap kutipan dari README tersebut.
Cara menginstal JitAPI MCP
Format diverifikasi 10 Nov 2026Instal JitAPI MCP di Claude Code
$ claude mcp add --env OPENAI_API_KEY=<YOUR_OPENAI_API_KEY> jitapi -- uvx jitapiInstal JitAPI MCP di Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Instal JitAPI MCP di VS Code
.vscode/mcp.json
{
"servers": {
"jitapi": {
"type": "stdio",
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Instal JitAPI MCP di Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Instal JitAPI MCP di Codex
~/.codex/config.toml
[mcp_servers.jitapi] command = "uvx" args = ["jitapi"] [mcp_servers.jitapi.env] OPENAI_API_KEY = "<YOUR_OPENAI_API_KEY>"
Instal JitAPI MCP di Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Tool JitAPI MCP 8
Terdeteksi dari READMEregister_apilist_apissearch_endpointsget_workflowget_endpoint_schemacall_apiset_api_authdelete_api
| register_api | — | |
| list_apis | — | |
| search_endpoints | — | |
| get_workflow | — | |
| get_endpoint_schema | — | |
| call_api | — | |
| set_api_auth | — | |
| delete_api | — |
Konfigurasi
OPENAI_API_KEYWajibRahasiaOpenAI API key for embeddings and workflow planning
GITHUB_TOKENOPENWEATHER_API_KEYVOYAGE_API_KEY
| Nama | Deskripsi | Tipe |
|---|---|---|
| OPENAI_API_KEY | OpenAI API key for embeddings and workflow planning | WajibRahasia |
| GITHUB_TOKEN | — | |
| OPENWEATHER_API_KEY | — | |
| VOYAGE_API_KEY | — |
Pengecekan otomatis
Berjalan 14 Nov 2026Laporan lengkap →Belum diverifikasi. Sebuah server memerlukan skor 80, tidak ada temuan serius, dan data yang cukup untuk kami periksa. Cara kerja checks
- Source repository terhubung dan dapat dijangkaunk3750/jitapi is public and reachablegithub.com/nk3750/jitapi ↗Lolos
- Paket menyebut repo ini sebagai sumbernyajitapi names nk3750/jitapi as sourcepypi.org/project/jitapi/ ↗Lolos
- Provenance build (atestasi Sigstore)No build attestation published for this releaseTidak diperiksa
- Lisensi open source (OSI)MITspdx.org/licenses/MIT.html ↗Lolos
- Ada commit atau release dalam satu tahun terakhirLast commit or release 2026-06-14github.com/nk3750/jitapi ↗Lolos
- OpenSSF ScorecardTidak diperiksa
- Nama package tidak mirip dengan package populerNo popular package one edit away from jitapiLolos
- Tidak ada advisory kritis di paket maupun dependensinyaCritical advisory: GHSA-36p7-vc44-83pf, GHSA-f4j7-r4q5-qw2cosv.dev/vulnerability/GHSA-36p7-vc44-83pf ↗Temuan
- Tidak ada instruksi tersembunyi untuk model8 tool descriptions and the README read; no override phrases, credential paths or hidden charactersLolos
- Tools yang bersifat destruktif telah diberi labelTidak diperiksa
- Endpoint remote menjawab handshake MCPTidak diperiksa
README
Lihat di GitHubJitAPI
Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically.
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 header, API key query param, or bearer token) |
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. Supported auth types: bearer, api_key (custom header), and api_key_query (query parameter). 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 (custom header, default X-API-Key), api_key_query (query parameter).
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
Built by Neelabh Kumar — AI engineer and builder.
Pertanyaan tentang JitAPI MCP
Bagaimana cara menambahkan JitAPI MCP ke Claude Code?
Jalankan claude mcp add --env OPENAI_API_KEY=<YOUR_OPENAI_API_KEY> jitapi -- uvx jitapi di terminal Anda. Tambahkan --scope user agar tersedia di semua proyek.
Bagaimana cara menambahkan JitAPI MCP ke Cursor?
Buka ~/.cursor/mcp.json dan tambahkan server di bawah mcpServers, menggunakan config Cursor yang ditunjukkan di bagian instalasi di atas.
Tool apa yang disediakan JitAPI MCP?
Server ini menyediakan 8 tool, termasuk register_api, list_apis, search_endpoints, get_workflow, get_endpoint_schema.
Apakah saya memerlukan API key untuk embeddings?
Tidak, JitAPI menggunakan local embeddings secara default, sehingga tidak memerlukan API key untuk fungsionalitas dasar.
Bagaimana JitAPI menangani spesifikasi API yang besar?
Alih-alih memuat seluruh spesifikasi ke dalam context, JitAPI menggunakan semantic search dan dependency graph untuk menampilkan endpoint yang hanya diperlukan saja.
Bisakah saya menggunakan beberapa API sekaligus?
Ya, Anda dapat mendaftarkan beberapa API dan mengajukan pertanyaan yang mencakup berbagai API tersebut, sehingga memungkinkan Claude untuk melakukan chaining call antar layanan yang berbeda.
Metode autentikasi apa saja yang didukung?
JitAPI mendukung bearer tokens, custom API key headers, dan API key query parameters.