Open Agent Search

Name: Open Agent Search
Author: jayanth-mkv

作者：jayanth-mkv版本 1.0.5i★ –i在你的电脑上运行

注册名称io.github.jayanth-mkv/open-agent-search

安装

概览

作者提供的说明（英文原文）

Search the web, news, images, videos and books, and extract page content for AI agents.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "open-agent-search": {
      "command": "npx",
      "args": [
        "-y",
        "open-agent-search",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add open-agent-search -- npx -y open-agent-search mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "open-agent-search": {
      "command": "npx",
      "args": [
        "-y",
        "open-agent-search",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "open-agent-search": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "open-agent-search",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 jayanth-mkv 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

星标数多于此分类中其他 7275 个服务器的 0%
发布到注册中心的时间比此分类中其他 7275 个服务器的 58% 更新
基础检查结果等于或优于此分类中其他 7275 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Open Agent Search 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（1.0.5）于27天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js, Python (uv)。

有什么可以替代它？

同一分类中有：Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者：upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新

安装

Codebase Memory

作者：DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新

安装

Exa

作者：exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Open Agent Search

One self-hostable search and content layer for AI agents and applications.

What is OAS? · Agent setup · Capabilities · Architecture · API surface · Contributing

Set up with your agent

Copy this prompt into your coding agent:

Set up Open Agent Search for this project using

https://github.com/Jayanth-MKV/open-agent-search. Read its README and skills/open-agent-search-setup/SKILL.md. Reuse uv if installed, otherwise install it using the official uv instructions for my OS. Configure the local stdio MCP server with the pinned package and managed Python version from the repository's MCP manifest. Merge the server into this agent's configuration without replacing existing servers. Install the open-agent-search-setup and open-agent-search skills for this agent in project scope. Verify the MCP connection and available tools, then try one web search. Tell me if a client restart is needed. No API key is required.

Installation commands

With Node.js 22+ and uv installed:

npx --yes open-agent-search@1.0.5 --version

npx --yes open-agent-search@1.0.5 mcp

Or start the HTTP API:

npx --yes open-agent-search@1.0.5 serve

The npm launcher uses the pinned Python core. It requires uv on PATH; uv manages Python 3.12 and dependencies.

With uv installed, run the MCP server in an isolated environment:

uvx --python 3.12 --from open-agent-search==1.0.5 oas-mcp

uv can download Python 3.12 when it is missing. The first run downloads dependencies; the client starts and stops this stdio process after configuration.

For a persistent PyPI installation and HTTP server:

uv tool install --python 3.12 open-agent-search==1.0.5

open-agent-search

The HTTP server listens on port 8000 on all interfaces. Use stdio for an agent that only needs local tools.

Install both skills for Codex in the current project:

npx --yes skills add Jayanth-MKV/open-agent-search --skill open-agent-search-setup open-agent-search --agent codex --copy --yes

Replace codex with claude-code, cursor, opencode, or your supported agent. Add --global only for installation across projects. Plugin and manual setup. Use either npm or PyPI above; both start the same Python implementation.

In Claude Code 2.1.275+, install both skills and the MCP configuration in one step:

/plugin install open-agent-search --marketplace Jayanth-MKV/open-agent-search --scope project

What is Open Agent Search?

Open Agent Search (OAS) is an independent retrieval layer for AI agents and applications. It provides one consistent search and content surface across local and deployed integrations.

OAS replaces separate adapters for every search vertical with one consistent tool surface. Run it locally for a single coding agent or deploy the HTTP service for shared agent and application workloads.

Search sources, transports, and client integrations can evolve without changing the repository's core goal: give agents and applications a dependable retrieval boundary they can control.

Connect MCP or HTTP

Add search to Claude Code

claude mcp add oas -- uvx --python 3.12 --from open-agent-search==1.0.5 oas-mcp

Restart Claude Code, then ask it to search the web, news, images, videos, or books. The same uvx command works with Cursor, VS Code, Windsurf, OpenClaw, and other MCP clients.

Generic MCP configuration

"mcpServers": { "open-agent-search": { "command": "uvx", "args": ["--python", "3.12", "--from", "open-agent-search==1.0.5", "oas-mcp"] } } }

Run the HTTP API

uv tool install --python 3.12 open-agent-search==1.0.5

open-agent-search

Make a first search:

curl "http://localhost:8000/api/search/text?q=python+programming&max_results=5"

The server exposes REST endpoints at http://localhost:8000, interactive API docs at /docs, and streamable HTTP MCP at /ai/mcp.

Capabilities

One search layer, multiple transports. Use stdio MCP locally or serve REST and MCP over HTTP.
No provider API key required. Search is powered by the ddgs library.
Self-hostable. Run locally, in Docker, or deploy the HTTP service to Vercel.
Framework-independent. The protocol surface works across major MCP clients and agent stacks.
Production-minded defaults. Typed FastAPI routes, rate limiting, health checks, tests, and deployment guides are included.

Architecture

The local MCP command and the HTTP service share the same search and content capabilities. Choose the connection path that matches where the consuming agent or application runs.

Two deployment paths

Path	Command or endpoint	Best for
Local MCP	`uvx --python 3.12 --from open-agent-search==1.0.5 oas-mcp`	Giving a desktop or coding agent search with no persistent server
HTTP service	`open-agent-search`	Applications, shared agent environments, REST clients, and remote MCP

Search surface

Capability	REST endpoint	MCP availability
Text search	`GET /api/search/text`	Yes
Image search	`GET /api/search/images`	Yes
Video search	`GET /api/search/videos`	Yes
News search	`GET /api/search/news`	Yes
Book search	`GET /api/search/books`	Yes
Unified search	`GET /api/search/all`	Yes
Fetch one page	`GET /api/content/fetch`	Yes
Fetch multiple pages	`POST /api/content/fetch-multiple`	Yes

See the API reference and MCP tool reference for parameters and response shapes.

Privacy model

OAS does not require an OAS account or a search-provider API key, and it can run on infrastructure you control. Search queries still have to reach upstream search providers through DDGS, so this project should not be treated as an anonymity network. Review your deployment logs, network policy, and upstream-provider terms for sensitive workloads.

Install and deploy

From source

git clone https://github.com/jayanth-mkv/open-agent-search.git

cd open-agent-search uv sync uv run open-agent-search

Docker

docker compose up -d

Deployment details: Docker · Vercel

Documentation

Registries and agent discovery

Packages: npm and PyPI.
Local MCP bundle: Smithery. It runs on your machine and requires Node.js 22+ and uv.
MCP Registry namespace: io.github.jayanth-mkv/open-agent-search. The release workflow publishes server.json after both packages are available. Check the registry record.
Agent skills: Open Agent Search and setup are published on ClawHub. You can also install them from GitHub using the commands above. The skills.sh directory discovers skills through real installations; a repository alone does not guarantee a listing.
Glama: glama.json declares the GitHub maintainer. Directory submission and ownership verification require a separate Glama sign-in.

The npm path requires Node.js 22+ and uv. The PyPI path uses uv to manage Python 3.12. This project provides a local server and deployment code; it does not provide a shared hosted search endpoint.

The local MCPB bundle is built with python scripts/build_mcpb.py. It contains the pinned npm launcher and requires Node.js 22+ and uv on PATH. Its first launch downloads the Python core and dependencies. No credentials are bundled.

ClawHub distributes its skill copies under MIT-0, as required by that registry. This repository and its packages remain MIT licensed. GitHub Actions previews skill changes on pushes to main and publishes them on releases when CLAWHUB_TOKEN and the repository variable PUBLISH_CLAWHUB=true are configured. The workflow checks that the authenticated ClawHub owner matches the source repository owner.

Development

uv sync --group dev

uv run pytest uv run ruff check .

Open Agent Search is currently beta software. Bug reports and focused pull requests are welcome; see CONTRIBUTING.md.

License

MIT

Maintained by Xplormity Collective.

Open Agent Search

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“搜索与 AI 记忆”中的其他服务器比较i

常见问题

替代选择

Context7

Codebase Memory

Exa

作者的 README

Set up with your agent

Installation commands

Or start the HTTP API:

What is Open Agent Search?

Connect MCP or HTTP

Add search to Claude Code

Run the HTTP API

Capabilities

Architecture

Two deployment paths

Search surface

Privacy model

Install and deploy

From source

Docker

Documentation

Registries and agent discovery

Development

License