Open Agent Search

Name: Open Agent Search
Author: jayanth-mkv

by jayanth-mkvversion 1.0.5i★ –iRuns on your computer

Registry nameio.github.jayanth-mkv/open-agent-search

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account jayanth-mkv, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7275 servers in this category
Published to the registry more recently than 58% of the other 7275 servers in this category
Basic checks equal to or better than 100% of the other 7275 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Open Agent Search safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.5) reached the registry 27 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 21 days ago

Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

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