agentsearch-mcp

agentsearch-mcp

Remote MCP connector for AgentSearch API that exposes web search, instant answers, and URL-to-clean-text fetching as typed MCP tools for agents and RAG pipelines.

Category
访问服务器

README

agentsearch-mcp

A remote MCP (Model Context Protocol) connector for AgentSearch API — an LLM/MCP-native web toolkit for agents and RAG pipelines: web search (provider-abstracted SERP), keyless instant answers, and URL → clean text/markdown fetch ready for an LLM context window.

Live: https://agentsearch-mcp.vercel.app/mcp — 3 tools, one per AgentSearch /v1 endpoint. Since the upstream AgentSearch deployment is metered (RapidAPI/Apify) and gates /v1/* behind a RapidAPI proxy-secret guard, this connector authenticates its own outbound calls with that same secret (AGENTSEARCH_MCP_PROXY_SECRET, sent as the X-RapidAPI-Proxy-Secret header) and applies a soft per-IP rate limit (AGENTSEARCH_MCP_RATE_LIMIT, default 30 tool-calls/hour, in-memory) so the free MCP tier stays a discovery channel rather than an unmetered bypass of the paid listing — see lib/ratelimit.js.

What this is, and why it's a separate connector

AgentSearch API is a plain REST API. Any HTTP client can already call it directly. This repo exists because MCP clients (Claude, ChatGPT, and other MCP-aware agents) don't consume arbitrary REST APIs — they consume MCP tools. agentsearch-mcp is a thin adapter layer that:

  • Exposes each AgentSearch endpoint as a discoverable, typed MCP tool (name, description, zod input schema, annotations) that an LLM can reason about and call directly, instead of having to be taught the REST surface out-of-band.
  • Speaks the MCP streamable-HTTP transport at a single /mcp endpoint, so it can be registered as a connector in Claude, ChatGPT, or any other MCP client with one URL.
  • Does nothing else. It has no business logic of its own — every tool call is a pass-through fetch to AgentSearch, and the JSON response AgentSearch returns is handed back verbatim as the tool result.

Free discovery tier over a metered API

This connector is a free discovery/growth tier in front of the metered AgentSearch API. The upstream (agentsearch-api.vercel.app) is sold on RapidAPI/Apify; this MCP wrapper authenticates to it with the shared RapidAPI proxy secret and caps usage per-IP so it stays a taste-test rather than an unmetered path around the paid plans. Heavy/production volume should go through AgentSearch on RapidAPI/Apify.

Authentication: None on the MCP side (deliberate)

AgentSearch's data has no per-user dimension — it's public web data (SERP results, DuckDuckGo instant answers, cleaned page text). There is nothing to gate per-caller, so this connector intentionally ships with:

  • No OAuth, no login, no bearer tokens for the MCP caller
  • No Supabase / database
  • No demo-vs-real account split — every caller gets the same real, live data

api/mcp.js builds a fresh, stateless McpServer per request and serves it with zero MCP-caller auth checks. The only outbound auth is the upstream RapidAPI proxy secret described above, which the connector holds server-side.

Tool list

One tool per AgentSearch /v1 endpoint (from agentsearch-api/openapi.yaml; /api/health is intentionally not wrapped):

Tool AgentSearch endpoint Description
web_search GET /v1/search Web SERP via a provider-abstracted backend (Brave or Serper). Returns normalized results with position/title/url/snippet/domain.
instant_answer GET /v1/answer Keyless DuckDuckGo instant answer — definitions, entities, quick facts.
fetch_url GET /v1/fetch Keyless, SSRF-guarded URL → clean, boilerplate-free text or markdown for RAG.

All 3 tools are read-only and annotated { readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true } — none of them write anything, and all of them reflect live, externally-changing web data.

How it wraps agentsearch-api

Each tool handler does a plain fetch(\${AGENTSEARCH_MCP_API_BASE_URL}${path}`, ...)` against the real AgentSearch REST API and returns the parsed JSON as MCP tool-result content:

{ content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] }

The outbound request carries X-RapidAPI-Proxy-Secret: <AGENTSEARCH_MCP_PROXY_SECRET> so it passes the upstream guard on /v1/*. Upstream HTTP errors (4xx/5xx) are caught and surfaced as a typed MCP error result via an asError helper rather than crashing the request.

Environment variables

Var Default Purpose
AGENTSEARCH_MCP_API_BASE_URL https://agentsearch-api.vercel.app Upstream AgentSearch base URL (override for local/self-hosted testing).
AGENTSEARCH_MCP_PROXY_SECRET (empty) RapidAPI proxy secret, sent as X-RapidAPI-Proxy-Secret to pass the upstream /v1/* guard. Without it, guarded routes return 403.
AGENTSEARCH_MCP_RATE_LIMIT 30 Soft per-IP tools/call cap per hour (in-memory, per serverless instance).

Project layout

api/mcp.js       MCP endpoint (StreamableHTTPServerTransport, stateless, no MCP-caller auth)
api/health.js    GET /api/health
lib/tools.js     All 3 tool definitions (zod schemas + fetch-and-forward handlers, proxy-secret auth)
lib/ratelimit.js Soft per-IP tools/call rate limiter
local-server.js  Plain-Node http server for local dev / smoke testing (not deployed)
test/smoke.mjs   Real end-to-end smoke test (initialize, tools/list, tools/call)
vercel.json      Routes /mcp -> api/mcp.js, /health -> api/health.js
server.json      MCP registry manifest

Local development

npm install
npm run dev          # starts local-server.js on :3900
npm run smoke        # runs test/smoke.mjs against the local server

To exercise a real end-to-end fetch through the upstream guard, set the proxy secret first:

export AGENTSEARCH_MCP_PROXY_SECRET=<the RapidAPI proxy secret>
npm run dev &
npm run smoke

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