harbor
TypeScript MCP gateway that connects AI agents to backend APIs via the Model Context Protocol — pluggable auth, V8 sandbox execution, circuit breaker, and audit logging.
Install / Use
claude mcp add vijaydeepsinha -- npx -y github:vijaydeepsinha/harborIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of harbor
harbor scores 80/100 on our quality scale, 294th of 1,340 Development & Engineering skills we index (top 22%).
Its MCP Server is 5.7 KB long, well organised into 8 sections with 7 code examples: a solid amount of guidance for an agent.
It has 10 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated 10 days ago, so harbor is actively maintained.
- Our last check on 2026-09-22 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 85/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
harbor compared with similar skills
All 4 of these similar skills score higher than harbor; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| harbor (this skill)by vijaydeepsinha | 80 | 10 | 10d ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 85.2k | 9d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.7k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.2k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.1k | today | CLAUDE.md |
Frequently asked questions
- How do I install harbor?
- Run
claude mcp add vijaydeepsinha -- npx -y github:vijaydeepsinha/harbor. The install tabs above show the steps for each supported agent. - Which AI agents does harbor work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is harbor safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 85/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is harbor still maintained?
- The repository was last updated 10 days ago, so harbor is actively maintained.
Skill content
View source on GitHubHarbor
A production-grade Model Context Protocol (MCP) gateway that connects AI clients to your existing backend APIs — without modifying those APIs.
Read the full article on Medium →
The Problem
When an AI (Claude, Cursor, GPT) needs to interact with your backend APIs, it has no way to know what endpoints exist, what parameters they take, how to authenticate, or what business rules apply.
The standard fix — generating one MCP tool per endpoint — doesn't scale. A realistic API has hundreds of endpoints that overwhelm any AI context window.
Harbor takes a different approach: Code Mode. Instead of one tool per endpoint, the AI gets five general-purpose tools and writes JavaScript to interact with your API. The gateway runs that code in an isolated V8 sandbox, validates every call, and forwards it to your backend with proper auth and circuit breaking — all without changing a line of your API code.
AI client → Harbor → Your backend APIs
│
├── V8 sandbox isolation
├── Per-service auth (OAuth 2.1 / static token)
├── Circuit breaker + retry
└── Audit logging
Features
- Five MCP tools —
discover_services,discover_skills,get_skill_details,search_code,api_execute - V8 sandbox isolation — AI-written JavaScript cannot access the network, filesystem, or framework internals
- Pluggable auth —
static-token,oauth-introspection,jwt-validation(local JWKS, no AS round-trip),oauth-2.1(RFC 8414/OIDC auto-discovery) - OAuth 2.1 Protected Resource — RFC 9728 discovery metadata,
WWW-Authenticateon 401, full MCP auth flow - Pluggable backends — register custom token-cache backends without forking the codebase
- Per-service configuration — each service declares its own auth, circuit breaker, and spec source
- Zero API changes — your backend never changes; Harbor is a pure adapter
- Service skills — Markdown SOP files the AI reads before making API calls
- Circuit breaker — count-based, per endpoint, per service
- Structured audit logging — every
api_executecall logged with code, endpoints, duration, outcome - Streamable HTTP + stdio — both MCP transports supported
Quick Start
Prerequisites: Node.js 22+, npm 10+, native build tools (Xcode CLT on macOS / build-essential on Linux)
git clone https://github.com/vdssinha/harbor
cd harbor
npm install
Run the demo (three local backends + MCP gateway):
bash examples/demo/start.sh
Verify (E2E smoke test, stdlib only):
python3 tests/demo_e2e.py --start-services
Connect Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"harbor": {
"url": "http://127.0.0.1:3333/mcp",
"headers": { "Authorization": "Bearer <YOUR_BEARER_TOKEN>" }
}
}
}
Connect Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"harbor": {
"url": "http://127.0.0.1:3333/mcp",
"headers": { "Authorization": "Bearer <YOUR_BEARER_TOKEN>" }
}
}
}
Full setup guide → docs/getting-started.md
Documentation
| Guide | What it covers |
|-------|----------------|
| docs/getting-started.md | Full setup, demo walkthrough, Cursor integration |
| docs/service-onboarding.md | Adding services, full config.json reference |
| docs/skill-authoring.md | Writing skills — frontmatter, api.request() patterns, error handling |
| docs/configuration.md | All environment variables |
| docs/adapter-guide.md | Custom connectors — Redis, gRPC, GraphQL |
| docs/oauth-2.1-guide.md | OAuth 2.1 setup and auth strategies |
| docs/architecture.md | System design, layers, extension points |
| docs/tool-layer.md | MCP protocol, sandbox model, tool contracts |
| docs/request-lifecycle.md | End-to-end request trace |
| docs/faq.md | Troubleshooting and common questions |
| ROADMAP.md | Planned features and milestones |
Development
npm run dev # tsx watch — live reload
npm test # vitest — 312 unit + integration tests
npm run typecheck # tsc --noEmit (strict)
npm run build # tsc → dist/
Contributing
Contributions are welcome. See CONTRIBUTING.md for setup, coding guidelines, PR process, and good first issues.
License
Apache License 2.0 — see LICENSE.
By contributing you agree your contributions will be licensed under Apache 2.0.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
