OpenRouter

io.github.tsilva由 GitHub 账号 tsilva 发布v1.1.8更新于 Oct 24, 2026

MCP server providing access to 300+ AI models via OpenRouter

发布方自己的服务：370.ai — AI Gateway: 100+ Chat Models, Image & Speech Generation

已验证STDIO仅桌面媒体与设计 AI 与机器学习

服务详情

标识符: io.github.tsilva/mcp-openrouter
传输: STDIO
运行时: Desktop only
信任: Verified
发布于: Sep 16, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 tsilva。这并不表明该账号就是产品方。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.tsilva%2Fmcp-openrouter.svg)](https://sourceweft.com/mcp/io.github.tsilva%2Fmcp-openrouter?utm_source=readme&utm_medium=badge)

概览

AI 生成的概览

一个本地 MCP 服务器，让助手通过 OpenRouter 调用 300 多个 AI 模型，用于对话、图像生成、嵌入和模型查找。

可以做什么: 向 OpenRouter 对话模型发送提示或消息列表，并在助手会话中取回回复。根据提示生成一张图像，可选保存到你指定的绝对本地路径。为单个字符串或字符串列表生成嵌入向量。列出可用模型，可按视觉、图像生成、嵌入、工具调用或长上下文等能力筛选。搜索模型名称和标识，最多返回 20 个匹配项。
适用场景: 适合希望在一个助手会话中通过单一 OpenRouter 账户访问多家模型提供方的场景，例如比较模型、生成图像或生成嵌入，而无需分别安装各家集成。
运行要求: 以 Python 包形式通过 stdio 在本地运行（需 Python 3.10 及以上），通常用 uvx 启动。需要 OpenRouter 账户，并且所有工具调用都需要 OPENROUTER_API_KEY 环境变量。可选的 DEFAULT_TEXT_MODEL、DEFAULT_IMAGE_MODEL 和 DEFAULT_EMBEDDING_MODEL 变量用于提供默认模型。需要访问 OpenRouter 的网络连接。

安装前请注意

服务器需要你的 OpenRouter API 密钥，且每次工具调用都会在你的 OpenRouter 账户上产生费用。不要把密钥放在明文 .env 文件中，建议使用密钥管理工具。图像生成会写入你指定的绝对路径，使用前请确认该路径。提示、文本和图像会发送给 OpenRouter 及其背后的模型提供方。

安装

在 SourceWeft 中

打开控制台中的 OpenRouter，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照仓库中的启动说明。

README

[mcp-openrouter]
🚀 One MCP server for OpenRouter models 🚀

mcp-openrouter is a Python MCP server that lets Codex, Claude Code, opencode, and other MCP hosts call OpenRouter models from local stdio tools.

It exposes chat, image generation, embeddings, model listing, and model search through a small FastMCP server with retry handling, host-aware installation, and optional default model environment variables.

Install

Install the published server into every detected MCP client:

Install into selected clients:

Run from a local checkout:

bash

git clone https://github.com/tsilva/mcp-openrouter.gitcd mcp-openrouteruv sync --devkeyenv doctorkeyenv run -- uv run mcp-openrouter

git clone https://github.com/tsilva/mcp-openrouter.gitcd mcp-openrouteruv sync --devkeyenv doctorkeyenv run -- uv run mcp-openrouter

mcp-openrouter with no arguments starts the stdio server. The explicit command is uv run mcp-openrouter serve.

Commands

bash

uvx mcp-openrouter install --yes                 # install into detected MCP clientsuvx mcp-openrouter install --yes --force         # replace an existing openrouter configuvx mcp-openrouter uninstall --yes               # remove from detected MCP clientsuv run mcp-openrouter                            # run the local stdio serveruv run pytest tests/test_cli.py tests/test_client.py tests/test_config.py tests/test_installer.py tests/test_release_metadata.py tests/test_server.pykeyenv run -- uv run pytest tests/test_tools.pyuv run ruff check src/uv run ruff format src/

uvx mcp-openrouter install --yes                 # install into detected MCP clientsuvx mcp-openrouter install --yes --force         # replace an existing openrouter configuvx mcp-openrouter uninstall --yes               # remove from detected MCP clientsuv run mcp-openrouter                            # run the local stdio serveruv run pytest tests/test_cli.py tests/test_client.py tests/test_config.py tests/test_installer.py tests/test_release_metadata.py tests/test_server.pykeyenv run -- uv run pytest tests/test_tools.pyuv run ruff check src/uv run ruff format src/

Tools

Tool	Purpose
`chat`	Send a prompt or message list to an OpenRouter chat model.
`generate_image`	Generate one image and optionally save it to an absolute local path.
`embed`	Generate embeddings for a string or list of strings.
`list_models`	List models, optionally filtered by `vision`, `image_gen`, `embedding`, `tools`, or `long_context`.
`find_models`	Search model names and slugs, returning up to 20 matches.

Example MCP prompts:

text

Use openrouter chat with anthropic/claude-sonnet-4 to summarize this fileUse openrouter generate_image with google/gemini-3-pro-image-preview to create a square app iconUse openrouter embed with mistralai/mistral-embed-2312 to embed "Hello world"Use openrouter list_models with capability "image_gen"Use openrouter find_models to search for "claude"

Use openrouter chat with anthropic/claude-sonnet-4 to summarize this fileUse openrouter generate_image with google/gemini-3-pro-image-preview to create a square app iconUse openrouter embed with mistralai/mistral-embed-2312 to embed "Hello world"Use openrouter list_models with capability "image_gen"Use openrouter find_models to search for "claude"

Configuration

OPENROUTER_API_KEY is required for all tool calls. For a local checkout, its .keyenv.toml maps the variable to macOS Keychain: use keyenv set OPENROUTER_API_KEY to replace it, keyenv doctor to verify it, and keyenv run -- ... to launch the server or live tests. Python still reads the value normally from os.environ.

Optional defaults make the model parameter optional for matching tools:

bash

DEFAULT_TEXT_MODEL=google/gemini-3-pro-image-previewDEFAULT_IMAGE_MODEL=google/gemini-3-pro-image-previewDEFAULT_CODE_MODEL=anthropic/claude-sonnet-4.5DEFAULT_VISION_MODEL=google/gemini-3-pro-image-previewDEFAULT_EMBEDDING_MODEL=mistralai/mistral-embed-2312

DEFAULT_TEXT_MODEL=google/gemini-3-pro-image-previewDEFAULT_IMAGE_MODEL=google/gemini-3-pro-image-previewDEFAULT_CODE_MODEL=anthropic/claude-sonnet-4.5DEFAULT_VISION_MODEL=google/gemini-3-pro-image-previewDEFAULT_EMBEDDING_MODEL=mistralai/mistral-embed-2312

The current tools read DEFAULT_TEXT_MODEL, DEFAULT_IMAGE_MODEL, and DEFAULT_EMBEDDING_MODEL. DEFAULT_CODE_MODEL and DEFAULT_VISION_MODEL are available for client conventions. Non-secret defaults may remain in .env; the API key must not.

Notes

Python 3.10+ is required.
The published runtime command installed into hosts is uvx mcp-openrouter.
Supported installer targets are Codex, Claude Code, and opencode.
generate_image.output_path must be absolute, for example /Users/you/output.png.
Unit tests mock network calls. tests/test_tools.py requires a live OPENROUTER_API_KEY.
After changing server code, restart the MCP host so it launches a fresh server process.
Keep server.json, CHANGELOG.md, and the package version in sync before release. The Makefile release helper is make release-x.y.z.

Local MCP Development

Claude Code:

bash

claude mcp add openrouter --scope user -- keyenv run --manifest /path/to/mcp-openrouter/.keyenv.toml -- uv run --directory /path/to/mcp-openrouter mcp-openrouter

claude mcp add openrouter --scope user -- keyenv run --manifest /path/to/mcp-openrouter/.keyenv.toml -- uv run --directory /path/to/mcp-openrouter mcp-openrouter

Codex:

bash

codex mcp add openrouter -- keyenv run --manifest /path/to/mcp-openrouter/.keyenv.toml -- uv run --directory /path/to/mcp-openrouter mcp-openrouter

codex mcp add openrouter -- keyenv run --manifest /path/to/mcp-openrouter/.keyenv.toml -- uv run --directory /path/to/mcp-openrouter mcp-openrouter

opencode:

json

{  "mcp": {    "openrouter": {      "type": "local",      "command": ["keyenv", "run", "--manifest", "/path/to/mcp-openrouter/.keyenv.toml", "--", "uv", "run", "--directory", "/path/to/mcp-openrouter", "mcp-openrouter"],      "enabled": true    }  }}

{  "mcp": {    "openrouter": {      "type": "local",      "command": ["keyenv", "run", "--manifest", "/path/to/mcp-openrouter/.keyenv.toml", "--", "uv", "run", "--directory", "/path/to/mcp-openrouter", "mcp-openrouter"],      "enabled": true    }  }}