Jitapi
概览
作者提供的说明(英文原文)
Turn any OpenAPI spec into an executable agent interface using graphs and semantic search.
PopNx MCP 的三大支柱
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i1 项中通过 1 项依据公开信息检查;尚未扫描代码
- 使用情况i非常新↓ 26/周 · ★ –
它能帮你做什么
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
- 连接方式: 在你的电脑上运行
- 传输方式: stdio
- 分类: 搜索与 AI 记忆
- 你需要填写:OPENAI_API_KEY
安装
选择你使用的 AI 应用,然后复制设置。
安装之前
- 基础检查:1 项中通过 1 项
- 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
- 需要你自己填写:
OPENAI_API_KEY
标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
- PyPI已安装 Python 的 uv(用于 uvx 命令)
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add jitapi --env OPENAI_API_KEY=your-value -- uvx jitapi运行前请先填写空着的值。
或者自己复制设置
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"jitapi": {
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
或者自己复制设置
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"jitapi": {
"type": "stdio",
"command": "uvx",
"args": [
"jitapi"
],
"env": {
"OPENAI_API_KEY": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
需要你填写的值
- OpenAI API key for embeddings and workflow planning
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它能做什么
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 nk3750 验证,该账户拥有此仓库
- … 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
- … 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与“搜索与 AI 记忆”中的其他服务器比较i
- 星标数多于此分类中其他 5686 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 5686 个服务器的 2% 更新
- 基础检查结果等于或优于此分类中其他 5686 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
常见问题
Jitapi 安全吗?
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
它需要哪些密钥或代码?
你需要填写:OPENAI_API_KEY
它在我的电脑上运行还是在云端?
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
它还在维护吗?
GitHub 仓库最后更新于–,最新版本(0.1.1)于10个月前进入注册中心。
哪些应用可以使用它?
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
有什么可以替代它?
同一分类中有:Context7, Codebase Memory, Exa
替代选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Exa
Connect AI agents to Exa for web search, content fetching, and multi-step research.
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
JitAPI
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.