Skill Bridge MCP

An open-source, read-only MCP server for discovering and loading Agent Skills stored as SKILL.md files. A skill can change on disk without rebuilding the server: the next MCP call sees the latest content.

This project is community-maintained and not an official OpenAI product.

What it does

Skill Bridge does not execute scripts, grant agent permissions, or dispatch jobs. The calling agent applies the loaded skill as lower-trust workflow guidance, using only the tools it already has permission to use. Never treat server-supplied skill text as system instructions.

Related MCP server: ThirdBrain skills-mcp

Quick start

Node.js 20+ is required.

git clone https://github.com/iiinno/skill-bridge-mcp.git
cd skill-bridge-mcp
npm ci
npm test
npm start

Local endpoints:

• MCP: http://127.0.0.1:8787/mcp (Streamable HTTP)

• Health: http://127.0.0.1:8787/health

The bundled sample library includes research-brief and code-review. Example calls: "Use Skill Bridge to list the skills" → "Load research-brief".

Add a skill

skill-library/
  my-skill/
    SKILL.md
    references/
      guide.md

Required frontmatter:

---
name: my-skill
description: Describe the workflow and when an agent should use it.
---

Directory names follow the Agent Skills specification (lowercase letters, digits, single hyphens, max 64 characters). The frontmatter name must match the directory name. Changes become visible on the next read, with no restart.

To use another library, set SKILL_BRIDGE_SKILLS_DIR to an absolute directory.

Private deployment with Secure MCP Tunnel

The recommended setup runs the MCP server only on loopback and uses an outbound OpenAI Secure MCP Tunnel to let ChatGPT access it without exposing an inbound port.

Ubuntu VPS (systemd user services): docs/VPS.md
Windows (CoS-bundled tunnel-client): TUNNEL-SETUP.md

For Skills Manager, the VPS can maintain a separate read-only private Git mirror with a dedicated SSH deploy key and five-minute systemd timer. The mirror lives outside this public repository. See docs/SKILLS-MANAGER.md.

Memory and Markdown integrations: read_github_markdown reads one GitHub Markdown document and returns its source revision. A private, opt-in SKILL_BRIDGE_MEMORY_DIR activates memory proposals, manual approval and approved-note search. These features do not automatically ingest all ChatGPT conversations or write to an existing AgentMemory DB. See docs/AGENT-MEMORY.md.

New standalone Markdown-first memory: set SKILL_BRIDGE_MARKDOWN_MEMORY_DIR to enable a minimal file-based memory system on your own VPS. Its .md files are the canonical data; no Mem0/Hindsight/PostgreSQL/embedding API is required. It is independent of the previous JSON review queue and the local AgentMemory database. See docs/MARKDOWN-MEMORY.md.

Create a dedicated Tunnel ID for Skill Bridge; do not run the same Tunnel ID on two hosts at the same time. Secure MCP Tunnel uses a runtime Platform API key; it does not require calling a paid inference API to load skills. Check Platform's own service terms separately.

Environment

If you deliberately make the MCP server externally reachable, you must implement HTTPS and a supported authentication flow such as OAuth 2.1. An unprotected public tunnel or fixed Bearer token is not a substitute for a secure ChatGPT OAuth integration.

Security

• Loopback binding by default; only the files under the controlled library are available.

• Rejects symlink traversal, invalid paths, oversized text files, and unsupported resource extensions.

• Explicit Host and Origin validation helps protect local deployment from DNS rebinding.

• Never put secrets or private data inside SKILL.md; connected ChatGPT clients can read them.

• Only trusted administrators should be able to modify the skill-library directory.

• No code execution is implemented.

• Loading an arbitrary skill creates a prompt-injection surface: the agent should keep the retrieved instructions below the user and system instruction hierarchy.

• Secure MCP Tunnel exposes the skill library to the chosen ChatGPT workspace; configure the appropriate organization/workspace permissions.

Limitations

• Maximum 2,048 skills are indexed in one call; optional limit and ranked search are supported, but pagination and separate accounts are not implemented.

• Only text references under references/ and assets/ are supported.

• Modifications to a skill require a fresh MCP call: they do not hot-replace model context already read.

• Actual ChatGPT registration is performed in ChatGPT's Plugins interface; nothing is silently installed in an account.

Development

npm ci
npm test

License: MIT. Contributions and issues are welcome.

日本語: 本ソフトは、サーバーに保存した Agent Skills を ChatGPT などの MCP クライアントから動的に読み取るためのOSSです。スキルそのものの実行や権限付与は行いません。常時運用は Ubuntu VPS手順、Windowsでの試用は トンネル接続手順 を参照してください。