custom-mcp-server

custom-mcp-server

Production MCP server for data annotation workflows, exposing six tools backed by AWS S3, DynamoDB, and Slack with JWT auth, rate limiting, and exponential-backoff retries.

Category
访问服务器

README

custom-mcp-server

A production Model Context Protocol server for a data-annotation workflow. It exposes six tools over the MCP stdio transport, backed by AWS S3 + DynamoDB and Slack, with JWT auth, per-tool rate limiting, and exponential-backoff retries.

Prerequisites

  • Node.js 20 LTS
  • npm
  • AWS account (S3 bucket + DynamoDB table) and a Slack bot token for runtime use (not required to run the test suite — all external calls are mocked)

Install

npm install

Environment setup

Copy .env.example to .env and fill in the values. Keys:

Key Required by Notes
AWS_REGION all AWS tools e.g. us-east-1
AWS_ACCESS_KEY_ID all AWS tools secret — keep out of source control
AWS_SECRET_ACCESS_KEY all AWS tools secret
S3_BUCKET_NAME s3_upload, s3_download default bucket
DYNAMO_TABLE_NAME dynamo_read/write, annotation_status table with partition key id
SLACK_BOT_TOKEN slack_notify, annotation_status secret, xoxb-...
SLACK_DEFAULT_CHANNEL slack_notify, annotation_status e.g. #annotations
OAUTH_ISSUER auth (every call) expected iss claim
OAUTH_AUDIENCE auth (every call) expected aud claim
JWKS_URI auth (RS256) JWKS endpoint for signature verification
JWT_SECRET auth (HS256, dev only) optional; ≥ 32 chars; refused when NODE_ENV=production
NODE_ENV auth set to production to force RS256/JWKS and forbid HS256
RATE_LIMIT_PER_MIN rate limiter default 100
RETRY_MAX_ATTEMPTS retry default 3
RETRY_BASE_DELAY_MS retry default 200
LOG_LEVEL logger debug/info/warn/error, default info

Build / test / run

npm run build       # compile TypeScript to dist/
npm run typecheck   # tsc --noEmit
npm test            # Jest (ESM) — all external calls mocked
npm start           # node dist/server.js (stdio transport)

Tools

Tool Input (required**) Required scope Behavior
s3_upload key, contentBase64, contentType? s3:write Upload base64 content to S3 under the caller's prefix; returns { bucket, key, etag }
s3_download key** s3:read Download object from the caller's prefix; returns { bucket, key, contentBase64, contentType }
dynamo_read id**, consistentRead? dynamo:read Read a record the caller owns; returns the item (without owner) or { found: false }
dynamo_write id, attributes, overwrite? dynamo:write Put a record stamped with the caller as owner; can only overwrite records the caller owns
slack_notify message**, channel?, threadTs? slack:write Post to Slack (text sanitized); returns { channel, ts }
annotation_status taskId**, newStatus?, notify? annotation:read (+ annotation:write to update) Read/update a task the caller owns, optionally notify Slack

Auth model

Every tool call is authenticated and authorized:

  • Authentication. The caller supplies a JWT via _meta.authorization (optionally Bearer-prefixed). The expected algorithm is pinned from server configuration — not the token header — to block algorithm-confusion attacks: RS256 (verified against JWKS_URI) by default, or HS256 only when a JWT_SECRET (≥ 32 chars) is set and NODE_ENV is not production. The server checks iss/aud/expiry (with a small clock skew) and derives an AuthContext (subject, scopes). Invalid tokens → AUTH_INVALID.
  • Scope authorization. Each tool declares requiredScopes. A token missing a required scope is rejected with FORBIDDEN before the handler runs.
  • Object-level authorization (ownership). DynamoDB records carry an owner attribute and S3 keys are confined to a per-subject prefix (<subject>/…). Callers can only read/update their own records and objects; foreign records are reported as not-found to avoid ID enumeration. This prevents IDOR.
  • Error handling. Callers receive only a stable error code plus a requestId; full error detail is logged server-side (stderr) and never leaked to the client.

JWKS keys are fetched through a cached, rate-limited client to avoid a network round-trip (and IdP DoS) on every verification. S3 up/downloads are capped at 10 MiB to bound memory use.

Rate limiting & retries

  • Rate limit: 100 requests/min per principal+tool (configurable), in-memory per process, keyed by subject:tool so one caller cannot starve others. Unknown tool names are rejected before consuming limiter budget. Exceeding it yields RATE_LIMITED.
  • Retry: transient failures (retryable: true) are retried up to 3 times with exponential backoff (baseDelay * 2^(n-1)). Conflicts, validation, and auth errors are never retried.
  • Idempotency note: retries wrap non-idempotent writes (dynamo_write, slack_notify). Only transient errors are retried, but adding idempotency keys is recommended future work.

Cursor setup

.cursor/mcp.json registers the server with Cursor:

{
  "mcpServers": {
    "custom-mcp-server": {
      "command": "node",
      "args": ["dist/server.js"],
      "env": { "AWS_REGION": "us-east-1", "...": "..." }
    }
  }
}

Secrets (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, SLACK_BOT_TOKEN, JWT_SECRET) are not placed in mcp.json; provide them via your shell environment / .env. Run npm run build before launching so dist/server.js exists.

Architecture

See PLAN.md for the full milestone plan, interface contracts, and blocker analysis. Source layout:

src/
  server.ts            stdio transport + tool-call pipeline
  config.ts            env loading + validation (zod)
  types.ts             shared interface contracts
  errors.ts            AppError exception + guards
  security.ts          scopes, ownership, key-scoping & sanitization helpers
  logger.ts            stderr-only structured logger
  auth/oauth.ts        JWT validation (algorithm-pinned) + cached JWKS
  middleware/          retry.ts, rate-limiter.ts
  clients/             s3/dynamo/slack factories
  tools/               one file per tool + index.ts

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选