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Jitapi

作者:nk3750版本 0.1.1i★ –i在你的电脑上运行
注册名称io.github.nk3750/jitapi

安装

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。

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

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。

在 Cursor 中打开

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。

在 VS Code 中打开

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 机密 必填 env
    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6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 7229 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7229 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 7229 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:★ 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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT3天前更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT44天前更新
安装

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

  1. Register — Parse an OpenAPI spec, build a dependency graph (which endpoints need data from which other endpoints), and create searchable embeddings for all endpoints
  2. Search — When you ask a question, JitAPI embeds your query and finds the most relevant endpoints via cosine similarity
  3. 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")
  4. Execute — Claude gets the endpoint schemas and makes the API calls, passing data between steps

MCP Tools

ToolDescription
register_apiRegister an API from an OpenAPI spec URL
list_apisList all registered APIs and their endpoint counts
search_endpointsSemantic search across endpoints using natural language
get_workflowFind relevant endpoints with dependency resolution and full schemas
get_endpoint_schemaGet the complete schema for a specific endpoint
call_apiExecute a single API call with auth, path params, query params, and body
set_api_authConfigure authentication (API key header, API key query param, or bearer token)
delete_apiRemove 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:

OSConfig 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:

ProviderQualitySetup
Local (default)GoodNothing — works immediately
Voyage AI (recommended)Excellentpip install jitapi[voyage] + set VOYAGE_API_KEY
OpenAIExcellentpip install jitapi[openai] + set OPENAI_API_KEY
CohereVery goodpip 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 passing credential directly, secrets are stored as plaintext JSON at ~/.jitapi/auth.json (file permissions 0600, directory 0700). For production use, prefer the env_var approach.

Environment Variables

VariableRequiredDescription
VOYAGE_API_KEYNoVoyage AI API key (recommended cloud provider)
OPENAI_API_KEYNoOpenAI API key (alternative cloud provider)
COHERE_API_KEYNoCohere API key (alternative cloud provider)
JITAPI_STORAGE_DIRNoData directory (default: ~/.jitapi)
JITAPI_LOG_LEVELNoDEBUG, 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.

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