GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Turn OpenAPI / Postman specs into runnable MCP servers, or serve any API as live MCP tools.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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": {
"api-translator": {
"command": "npx",
"args": [
"-y",
"mcp-api-translator"
]
}
}
}在终端中运行这条命令
claude mcp add api-translator -- npx -y mcp-api-translator粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"api-translator": {
"command": "npx",
"args": [
"-y",
"mcp-api-translator"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"api-translator": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mcp-api-translator"
]
}
}
}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。
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。
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10日
注册名称已通过 GitHub 账户 krishgok 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
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)。
GitHub 仓库最后更新于–,最新版本(0.4.1)于30天前进入注册中心。
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 Node.js。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
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。
An MCP server that generates MCP servers. Give it an API definition — OpenAPI 3.0/3.1 or a Postman collection — and it scaffolds a complete, runnable, _ownable_ TypeScript or Python MCP server for that API.
_Above: curating Firecrawl's 20 operations down to 6, appending the Gmail API to the same server, then an agent calling the self-hosted result. Counts, tool names and paths come from real runs against the published Firecrawl and Gmail descriptions; the API responses are illustrative — the recording runs against a local stub, not live Firecrawl or Gmail accounts._
Turning an OpenAPI spec into MCP "tool stubs" is not novel — FastMCP's from_openapi, Speakeasy/Gram, and several openapi-mcp-generator projects already do the mechanical part. A naive endpoint→tool generator has no real advantage. This project focuses on the parts those tools skip:
1. Curation, not just generation. A 200-endpoint API naively becomes 200 tools, which wrecks a model's tool-selection accuracy and blows out context. analyze_spec previews the tool list before anything is written, every command takes includeTags / methods / pathGlob / excludeOperations, and you get a warning when a server grows past 40 tools.
2. Aggregation via append. extend_mcp_server adds another API's tools to an existing project, so you can build one MCP server spanning Firecrawl + Gmail + your internal API. Credentials stay separate: each API also reads namespaced env vars derived from its title.
3. An artifact you own. Output is a normal project, not a hosted black box — readable per-tool files, env-based auth, a Dockerfile, and a server.json plus client snippets for publishing to the official MCP Registry.
If you only need throwaway, in-memory exposure of one API and don't care about owning the code, FastMCP's runtime mode may suit you better — that's a deliberate non-goal here.
No install step. npx fetches and runs the latest published version — cross-platform, Node 20+.
Claude Code does not read claude_desktop_config.json — it keeps its own MCP config:
claude mcp add api-translator -- npx -y mcp-api-translator
That registers it at local scope. Use -s user for all your projects, or commit a project-scoped .mcp.json to share it. Verify with claude mcp list.
Add to claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json):
{
"mcpServers": { "api-translator": { "command": "npx", "args": ["-y", "mcp-api-translator"] } } }
Cursor, Cline, Continue.dev, Docker
Cursor — ~/.cursor/mcp.json (or project-scoped .cursor/mcp.json), same mcpServers shape as Claude Desktop above.
Cline (VS Code) — sidebar → MCP Servers → Configure, same shape plus "disabled": false.
Continue.dev — ~/.continue/config.json, under experimental.modelContextProtocolServers, as a { transport: { type: "stdio", command, args } } entry.
Docker (no Node required):
{
"mcpServers": { "api-translator": { "command": "docker", "args": ["run", "--rm", "-i", "ghcr.io/krishgok/mcp-api-translator:latest"] } } }
To read specs from disk or write projects to a host path, mount the directory with -v ${PWD}:/workspace and pass /workspace/... as specPath / outputDir.
MCP config is read at startup, so restart your client — quit and reopen Claude Desktop, Cursor, …, or start a new session in Claude Code.
| Tool | What it does |
|---|---|
analyze_spec | Parse a spec and preview the tools that would be generated — no files written. |
generate_mcp_server | Generate a complete MCP-server project into outputDir. |
extend_mcp_server | Append another spec's tools to an existing project (idempotent). |
list_supported_features | Report supported formats, auth schemes, transports, and limits. |
All spec inputs accept inline text (spec) or a local path (specPath), JSON or YAML.
You don't call the tools by hand — you ask your agent, and it drives them.
1. Preview, then curate. See what a spec becomes before writing anything:
_"Analyze ./petstore.yaml and show me the proposed tools."_
_"Only the GET endpoints under /pets."_
analyze_spec({ specPath: "./petstore.yaml" });
// → proposed tool list, auth scheme, and the env vars the server will need
analyze_spec({ specPath: "./petstore.yaml", methods: ["GET"], pathGlob: "/pets/**" }); // also: includeTags: ["pets"], excludeOperations: ["deletePet"]
2. Generate, with the same filters plus an output directory:
generate_mcp_server({ specPath: "./petstore.yaml", outputDir: "./petstore-mcp" });
// options: language: "python", transport: "http", auth: {...}, force: true
3. Aggregate — add more APIs to the same server:
// any second API — the sources don't have to share a format or a vendor
extend_mcp_server({ projectDir: "./petstore-mcp", specPath: "./billing.postman.json", includeTags: ["invoices"], }); // idempotent; hand-edited tool files are preserved
Aggregated APIs don't share credentials: each also reads namespaced env vars ( _API_BASE_URL, _API_KEY, … — namespace derived from the API title) before falling back to the bare ones. The extend summary and .env.example list the exact names.
4. Run it. The output is a normal project you own:
cd petstore-mcp && npm install && npm run build
cp .env.example .env # set API_BASE_URL + credentials (never embedded in code) npm start
Register it with your client using the generated client-config.md, and your agent can call the APIs directly.
Full walkthrough with sample outputs and troubleshooting: [docs/usage-workflow.md](docs/usage-workflow.md).
language: "python"). mcp-api-translator serve --spec ./api.yaml
mcp-api-translator serve --spec ./a.yaml --spec ./b.yaml --methods GET,POST # aggregate
serve runs the same request plan and env-based auth the generator emits, so behavior matches generated output exactly — it just skips the codegen step. It speaks stdio by default, or stateless Streamable HTTP with --transport http --port 3000. Logs are structured JSON lines on stderr in containers, readable text on a TTY (LOG_LEVEL, LOG_FORMAT).
| Doc | What's in it |
|---|---|
| usage-workflow.md | End-to-end walkthrough, curation loop, auth setup, troubleshooting. |
| design.md | Tech stack, generated project layout, limitations, security model. |
| deploy-serve.md | Docker/compose recipes for serve, logging and observability. |
| serve-api-proposal.md | Design of the runtime proxy and the roadmap. |
| market-analysis.md | Why both generate and serve models exist. |
| CONTRIBUTING.md | Dev setup, PR conventions, DCO sign-off. |
Known limits at a glance:
Details and the security model: docs/design.md.
npm install
npm test # unit + integration (parsers, curation, emit, append) npm run typecheck npm run build npm run e2e # generate a sample project from the fixtures into build/e2e-out
Contributions welcome — see CONTRIBUTING.md. All commits must be signed off under the Developer Certificate of Origin (git commit -s).
mcp-api-translator is dual-licensed — © 2026 krishgok. Full details in LICENSING.md.
Redistributions must retain LICENSE and NOTICE. The licenses do not grant the right to use the "mcp-api-translator" name to endorse or promote forked or derivative works without prior written permission.