Which integrations are available for this server?

Provides a bridge that exposes an OpenAI-compatible /v1/chat/completions HTTP endpoint, allowing MCP tools to forward chat completion requests and responses with MCP-specific headers.

How do I use MCP Token Bridge?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Token Bridge forward this chat completion request to my local model endpoint" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCPTokenBridge

English Version · see Chinese version → 中文版本

What it is:

A single‑file bridge that lets you use private subscription power through public endpoints—without leaking secrets.
OpenAI‑compatible HTTP: /v1/chat/completions
Anthropic‑style shim: /v1/messages
An MCP hook that stays alive and drains queues.

Why it exists:

Convert private tokens (e.g., Copilot/MCP) into safe calls from any OpenAI/Anthropic client.
Stream replies with SSE; log RX/TX with per‑request GUIDs and full content on stream end.

Killer scenarios:

Resource sharing: team subscription, dev environments, no real token exposure.
Multi‑tenant proxy: temporary public tokens, scoped access, secrets sealed.
Audit + rate‑limit: RX/TX logs per call for monitoring and throttling.
Third‑party integrations: controlled, expiring access for partners.
Test/Sandbox: safe non‑prod tokens to validate features.

Quick start (Windows) — MCP‑driven launch only:

# 1) Create venv and install deps python -m venv .venv . .venv/Scripts/activate pip install -r requirements.txt # 2) Add an MCP config so Copilot starts the bridge # VS Code Settings or your MCP config file (example):

{ "mcpServers": { "MCPTokenBridge": { "transport": {"type": "stdio"}, "command": "python", "args": ["mcptb.py", "--host", "0.0.0.0", "--port", "8000"], "env": {"MCPTB_HTTP_TIMEOUT": "none"} } } }

# 3) Open Copilot Chat in VS Code to activate MCP (hook warms up) # 4) Verify HTTP is up (after warm‑up) curl -s http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"hi"}],"stream":false}'

Note: launching mcptb.py directly from the shell won’t attach to Copilot; the MCP must start it.

Force colors (optional):

$env:MCPTB_FORCE_COLOR="1"

Streaming:

OpenAI SSE data: chunks with choices[].delta
Anthropic events: message_start → content_block_delta → message_stop → [DONE]
The bridge collects fragments during streaming; full text is logged at completion.

Endpoints:

OpenAI non‑stream

curl -X POST http://127.0.0.1:8000/v1/chat/completions -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Hello"}],"stream":false}'

OpenAI stream

curl -N -X POST http://127.0.0.1:8000/v1/chat/completions -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Stream"}],"stream":true}'

Anthropic non‑stream

curl -X POST http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Hello"}],"stream":false}'

Anthropic stream

curl -N -X POST http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Stream"}],"stream":true}'

Models endpoint:

# Returns a simple OpenAI-style list of available models curl http://127.0.0.1:8000/v1/models

Notes:

The bridge currently exposes a single effective model. This endpoint exists for client compatibility.
Actual model selection is performed by the MCP client via preferences; see below.

Model preferences:

The bridge forwards model selection via MCP modelPreferences with a hint from the HTTP model field.
You can tune capability priorities via environment variables (0–1):
- MCPTB_PREF_INTELLIGENCE: favor capability
- MCPTB_PREF_SPEED: favor latency
- MCPTB_PREF_COST: favor price Example:

$env:MCPTB_PREF_INTELLIGENCE = "0.8" $env:MCPTB_PREF_SPEED = "0.5" $env:MCPTB_PREF_COST = "0.3"

Tokens and timeouts:

Max tokens forwarded to MCP sampling can be configured:
- MCPTB_MAX_TOKENS (default: 327680)
HTTP await timeout for hook completion:
- MCPTB_HTTP_TIMEOUT (seconds, or none/0/infinite/inf to disable) Example:

$env:MCPTB_MAX_TOKENS = "327680" $env:MCPTB_HTTP_TIMEOUT = "none"

Limits:

Actual generated length may be capped by the client‑selected model’s maximum context window and provider policies. The bridge forwards preferences and max_tokens, but final selection and enforcement is done by the MCP client and its provider.

MCP setup:

{ "mcpServers": { "MCPTokenBridge": { "transport": {"type": "stdio"}, "command": "python", "args": ["mcptb.py", "--host", "0.0.0.0", "--port", "8000"], "env": {"MCPTB_HTTP_TIMEOUT": "none"} } } }

Advanced MCP config (env examples):

{ "mcpServers": { "MCPTokenBridge": { "transport": {"type": "stdio"}, "command": "python", "args": ["mcptb.py", "--host", "0.0.0.0", "--port", "8000"], "env": { "MCPTB_HTTP_TIMEOUT": "none", "MCPTB_MAX_TOKENS": "327680", "MCPTB_PREF_INTELLIGENCE": "0.8", "MCPTB_PREF_SPEED": "0.5", "MCPTB_PREF_COST": "0.3", "MCPTB_FORCE_COLOR": "1" } } } }

Notes:

Single‑file runtime (mcptb.py), strong typing, minimal deps.
MCP warm‑up required; until ready, HTTP returns 503.
GUID‑tagged RX/TX logs; set MCPTB_FORCE_COLOR=1 for ANSI colors.
Unified per‑request queues for stream/non‑stream; final TX logs include full content.

WSL2 → Windows:

ip route | awk '/default/ {print $3}' grep nameserver /etc/resolv.conf | awk '{print $2}'

License:

Operational clarity over legal boilerplate. Use responsibly.

中文版本

查看英文版本 → English Version

项目简介：

单文件桥接：把私有订阅能力通过公开接口安全暴露。
OpenAI 兼容 HTTP：/v1/chat/completions
Anthropic 风格兼容：/v1/messages
常驻 MCP hook：持续消费队列并返回结果。

存在意义：

将私有 Token（如 Copilot/MCP）转换为可被 OpenAI/Anthropic 客户端调用的安全请求。
支持流式 SSE；RX/TX 日志带 GUID，流结束时记录完整文本。

高价值场景：

订阅资源共享：团队订阅，开发/测试环境复用，避免暴露真实凭证。
多租户安全代理：按项目签发临时公开 Token，控制访问范围，核心凭证不外泄。
审计与限流：对每次调用记录 RX/TX（含 GUID），实现精细化监控与限流。
第三方集成：为合作方提供可控、带有效期的访问权限，而非企业主 Token。
测试与沙箱：在非生产环境用受控公开 Token 安全验证功能。

快速开始（Windows）— 必须由 MCP 驱动启动：

# 1）创建虚拟环境并安装依赖 python -m venv .venv . .venv/Scripts/activate pip install -r requirements.txt # 2）在 VS Code 中配置 MCP，让 Copilot 启动桥接器

{ "mcpServers": { "MCPTokenBridge": { "transport": {"type": "stdio"}, "command": "python", "args": ["mcptb.py", "--host", "0.0.0.0", "--port", "8000"], "env": {"MCPTB_HTTP_TIMEOUT": "none"} } } }

# 3）打开 VS Code 的 Copilot Chat 以激活 MCP（hook 预热就绪） # 4）预热完成后，使用 curl 验证 HTTP 服务 curl -s http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"hi"}],"stream":false}'

注意：直接在命令行启动 mcptb.py 无法挂接到 Copilot，必须由 MCP 启动。

可选：在非 TTY 输出中强制彩色日志：

$env:MCPTB_FORCE_COLOR="1"

流式说明：

OpenAI：SSE data: 行携带 choices[].delta
Anthropic：message_start → content_block_delta → message_stop → [DONE]
桥接器在流式过程中累计片段，结束时输出完整文本到 TX 日志。

接口示例：

OpenAI 非流式

curl -X POST http://127.0.0.1:8000/v1/chat/completions -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Hello"}],"stream":false}'

OpenAI 流式

curl -N -X POST http://127.0.0.1:8000/v1/chat/completions -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Stream"}],"stream":true}'

Anthropic 非流式

curl -X POST http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Hello"}],"stream":false}'

Anthropic 流式

curl -N -X POST http://127.0.0.1:8000/v1/messages -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"Stream"}],"stream":true}'

模型列表接口：

# 返回 OpenAI 风格的模型列表（兼容用） curl http://127.0.0.1:8000/v1/models

说明：

当前桥接器仅暴露一个有效模型；此接口用于满足客户端的模型枚举需求。
实际模型选择由 MCP 客户端根据偏好完成，见下文。

模型偏好：

桥接器把 HTTP 请求体中的 model 作为 MCP modelPreferences.hints 传递，并可配置三项优先级：
- MCPTB_PREF_INTELLIGENCE：能力优先（0–1）
- MCPTB_PREF_SPEED：时延优先（0–1）
- MCPTB_PREF_COST：成本优先（0–1）示例：

$env:MCPTB_PREF_INTELLIGENCE = "0.8" $env:MCPTB_PREF_SPEED = "0.5" $env:MCPTB_PREF_COST = "0.3"

Tokens 与超时：

采样的最大 tokens：
- MCPTB_MAX_TOKENS（默认：327680）
HTTP 等待超时（秒），可关闭：
- MCPTB_HTTP_TIMEOUT（数值或 none/0/infinite/inf）示例：

$env:MCPTB_MAX_TOKENS = "327680" $env:MCPTB_HTTP_TIMEOUT = "none"

限制说明：

最终生成长度受客户端所选模型的最大上下文窗口以及提供方策略限制。桥接器会传递偏好与 max_tokens，但实际选择与限制由 MCP 客户端及其提供方决定。

MCP 配置：

{ "mcpServers": { "MCPTokenBridge": { "transport": {"type": "stdio"}, "command": "python", "args": ["mcptb.py", "--host", "0.0.0.0", "--port", "8000"], "env": {"MCPTB_HTTP_TIMEOUT": "none"} } } }

高级 MCP 配置（env 示例）：

注意事项：

单文件运行（mcptb.py）、强类型、最小依赖。
MCP 会话需预热；未就绪时 HTTP 返回 503。
RX/TX 日志带 GUID；设置 MCPTB_FORCE_COLOR=1 可强制 ANSI 彩色。
流式与非流式通过每请求队列统一管理；最终 TX 日志包含完整内容。

WSL2 访问 Windows：

ip route | awk '/default/ {print $3}' grep nameserver /etc/resolv.conf | awk '{print $2}'

许可证：

更关注可运行性与清晰性；请负责任地使用。

MCP Token Bridge

MCPTokenBridge

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