Codesearch

Name: Codesearch
Author: SK-DEV-AI

by SK-DEV-AIversion 1.0.1i★ –iRuns on your computer

Registry nameio.github.SK-DEV-AI/codesearch

Install

Overview

Description from the maker (original English)

Code, package, docs, paper and vulnerability search. 17 tools, keyless lanes.

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
You need to fill in: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

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).
You fill in yourself: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx 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": {
    "codesearch": {
      "command": "uvx",
      "args": [
        "skdev-codesearch-mcp"
      ],
      "env": {
        "GROQ_API_KEYS": "your-value",
        "TAVILY_KEYS": "your-value",
        "NV_KEY": "your-value",
        "SE_KEY": "your-value",
        "S2_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add codesearch --env GROQ_API_KEYS=your-value --env TAVILY_KEYS=your-value --env NV_KEY=your-value --env SE_KEY=your-value --env S2_KEY=your-value -- uvx skdev-codesearch-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "codesearch": {
      "command": "uvx",
      "args": [
        "skdev-codesearch-mcp"
      ],
      "env": {
        "GROQ_API_KEYS": "your-value",
        "TAVILY_KEYS": "your-value",
        "NV_KEY": "your-value",
        "SE_KEY": "your-value",
        "S2_KEY": "your-value"
      }
    }
  }
}

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": {
    "codesearch": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "skdev-codesearch-mcp"
      ],
      "env": {
        "GROQ_API_KEYS": "your-value",
        "TAVILY_KEYS": "your-value",
        "NV_KEY": "your-value",
        "SE_KEY": "your-value",
        "S2_KEY": "your-value"
      }
    }
  }
}

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.

Values you fill in

GROQ_API_KEYS secret env
Optional. Groq keys for synthesis and query rewriting.
TAVILY_KEYS secret env
Optional. Tavily search lane.
NV_KEY secret env
Optional. NVIDIA embeddings for ranking.
SE_KEY secret env
Optional. Stack Exchange key (10k/day instead of 300).
S2_KEY secret env
Optional. Semantic Scholar key (1 RPS).

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SK-DEV-AI, 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 7240 servers in this category
Published to the registry more recently than 73% of the other 7240 servers in this category
Basic checks equal to or better than 100% of the other 7240 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 Codesearch 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?

You need to fill in: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

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 (1.0.1) reached the registry 14 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need 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 3 days ago

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 20 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 44 days ago

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.

codesearch MCP Server

mcp-name: io.github.SK-DEV-AI/codesearch

Companion agent skills: SK-DEV-AI/skills · npx skills add SK-DEV-AI/skills

Code, package, docs, and paper search MCP server. Per-package source navigation (npm/PyPI/crates), per-repo intelligence (GitHub URL or owner/repo), Q&A communities, vulnerability data, documentation, and academic papers — with embedding dedup and a local cross-encoder reranker.

Tools (17)

analyze — Start here for unfamiliar repos: GitHub metadata + code quality + wiki architecture in one call (10–15s).
search_all — Broad multi-source discovery (Context7, GitHub, DeepWiki, CodeWiki, SO, HN, Libraries.io, npm, DevDocs, Semantic Scholar, Tavily…). For surgical single-source work call the tool below directly.
code_search — Search code/docs/symbols across indexed dependencies (target=npm:express). npm/PyPI/crates only — for GitHub repos use searchcode or analyze.
code_files / code_read — List files / read a file in an indexed dependency by package spec.
searchcode — Per-repo intelligence: analyze (overview), search (code within the repo), findings (quality issues), file_tree, get_file. Needs repository for every action. Free, no auth.
wiki — Repo architecture Q&A via DeepWiki + CodeWiki. Single repo (owner+repo) or up to 10 repos (repos).
search_package — Raw registry queries: versions, dist-tags, deps.dev graphs, advisories (version='latest' OK). For composite intelligence use pkg.
pkg — Composite package intelligence: metadata, changelog, upgrade review (vulns + changelog + deps diff), file list/read.
search_libraries — Libraries.io metadata and source rank. Compare dependency candidates, find the repo behind a package.
vulns — Sonatype Guide + keyless OSV.dev fallback: scan (needs platform+name+version), detail (needs vuln_id; enriched with NVD CVSS/CWE/references), latest_version/license (need purl).
docs — Docs with smart fallback (Context7 → ReadTheDocs → llms.txt → DevDocs); then fetch(url) or devdocs_fetch_content for full pages.
so_search — Stack Overflow: stackexchange (authoritative resolved answers) or sofa (fresher agent content, needs SOFA_KEY).
hn — Hacker News discussion and sentiment (search, stories, items, users).
papers — Academic papers. Prefer action=search (S2 → arXiv → OpenAlex → CORE fallback chain); arxiv_search is single-source and rate-limited.
enrich — Fetch full content for a result list from any search tool, dedup + rerank.
ping — Connectivity check. Use before expensive calls when uncertain.

Setup

Requires Python 3.14+.

python3 -m venv .venv && source .venv/bin/activate

pip install -r requirements.txt cp run.example run # fill in your API keys (run is gitignored — never commit it) chmod +x run

Point your MCP client at run (stdio):

{ "codesearch": { "command": "/path/to/codesearch/run" } }

API keys (`run`)

Key	Used for	Required?
`GITHUB_TOKEN`	GitHub API (repo ops, higher rate limits)	Recommended
`CONTEXT7_API_KEY`	Context7 docs	Optional
`TAVILY_KEYS`	Tavily lane in search_all	Optional
`S2_API_KEY`	Semantic Scholar (1 rps dedicated vs shared anonymous pool)	Optional
`SE_API_KEY` / `SOFA_KEY`	Stack Exchange / Stack Overflow for Agents	Optional
`LI_KEY`	Libraries.io	Optional
`OSS_TOKEN`	Sonatype OSS Index	Optional
`FIRECRAWL_KEYS`	Firecrawl fallback	Optional
`NV_KEY`	NVIDIA embedding endpoint	Optional

Install from PyPI

pip install skdev-codesearch-mcp          # core install, small

pip install skdev-codesearch-mcp[all] # + browser/OCR/extract extras (multi-GB)

The codesearch-mcp console script speaks MCP over stdio:

{ "codesearch": { "command": "codesearch-mcp" } }

Docker

docker build -t codesearch-mcp .

docker run --rm -i codesearch-mcp

Keys are passed at run time, never baked in: -e GROQ_API_KEYS=.... Heavy extras: docker build --build-arg EXTRAS="[all]" -t codesearch-mcp .

Notes

Reranker (optional, local): shared with the websearch server — one cross-encoder worker over a Unix socket. Without it, results return unranked; everything still works.
Caching: per-source file caches with TTLs; repeat queries are cheap.
Safety: all user-URL fetches are SSRF-validated (private-IP blocking + redirect-hop revalidation).

Codesearch

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

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

codesearch MCP Server

Tools (17)

Setup

API keys (run)

Install from PyPI

Docker

Notes

API keys (`run`)