Search, rank, and compare open-source AI projects using Archestack's curated rankings and GitHub data.
Also known as archestack/mcp, mcp, @archestack/mcp
- Stars
- 0
- Tools
- 7
- Downloads, 30 days
- 1,408
- Latest version
- 0.3.1
- Last commit
- Nov 13, 2026
- License
- MIT
What is Archestack MCP?
Archestack is an MCP server. Search, rank, and compare open-source AI projects using Archestack's curated rankings and GitHub data. It exposes 7 tools, such as search_projects, get_project, deploy_facts.
Summary generated from the project's README
About Archestack MCP server
Archestack provides a way for developers to query curated rankings and GitHub data for open-source AI projects. It covers two primary categories: self-hosted AI infrastructure like vector databases and agents, and tools for vibe coding such as coding agents and MCP servers. Users can access this information through a local installation using npm or via a hosted HTTP server. The hosted version is available at a specific URL for clients like Claude or Claude Code and operates under a limit of 120 requests per minute.
The server includes specific tools to search for projects based on hardware requirements like arm64 or no GPU, compare multiple projects side by side, and find open-source alternatives to paid software. It also provides safety checks by serving allowlists for administrators. Because it relies on a static open data API, no accounts or API keys are required to use the service. The system is designed to be read-only and maintains privacy by not logging user questions.
What you can do with it
- 1Find hardware-compatible AI toolsAsk for a list of vector databases that can run without a GPU.
- 2Compare competing open-source projectsRequest a side-by-side comparison of Open WebUI and LibreChat.
- 3Identify alternatives to paid softwareSearch for open-source options that serve as replacements for Cursor or ChatGPT.
- 4Verify repository safety before installationCheck the license and upkeep of a specific GitHub repository before downloading it.
Written from the project's README. Every use case is checked against a quote from it.
How to install Archestack MCP
Formats verified 10 Nov 2026Install Archestack MCP in Claude Code
$ claude mcp add mcp -- npx -y @archestack/mcpInstall Archestack MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"mcp": {
"command": "npx",
"args": [
"-y",
"@archestack/mcp"
]
}
}
}Install Archestack MCP in VS Code
.vscode/mcp.json
{
"servers": {
"mcp": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@archestack/mcp"
]
}
}
}Install Archestack MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"mcp": {
"command": "npx",
"args": [
"-y",
"@archestack/mcp"
]
}
}
}Install Archestack MCP in Codex
~/.codex/config.toml
[mcp_servers.mcp] command = "npx" args = ["-y", "@archestack/mcp"]
Install Archestack MCP in Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"mcp": {
"command": "npx",
"args": [
"-y",
"@archestack/mcp"
]
}
}
}Archestack MCP tools 7
Detected from the READMEsearch_projectsget_projectdeploy_factstop_in_categorycomparecheck_repoalternatives_to
| search_projects | — | |
| get_project | — | |
| deploy_facts | — | |
| top_in_category | — | |
| compare | — | |
| check_repo | — | |
| alternatives_to | — |
Automated checks
Ran Nov 12, 2026Full report →Passed our automated checks. That is not a security audit: read the code and give the server the narrowest access it needs. How checks work
- Source repository linked and reachablePass
- Open source license (OSI)Pass
- Commit or release in the last yearPass
- Package name not close to a popular packagePass
- Remote endpoint uses HTTPSPass
- Destructive tools are labelledPass
- No hidden instructions to the modelPass
- No critical advisory in the package or its dependenciesPass
README
View on GitHubArchestack MCP server
Ask your assistant about open-source AI projects and get answers from the Archestack rankings: scores, GitHub facts, reviews and open-source picks for paid tools.
It covers two lists:
- Best of AI: self-hosted AI apps and infrastructure, like chat UIs, model servers, RAG, agents and vector databases.
- Best of Vibe Coding: starters, coding agents, MCP servers, skills and plugins for building with AI.
It reads the open data API. No key, no account. Run it on your machine with npm, or add the hosted server by its URL.
Hosted server
https://mcp.archestack.com/mcp: the same tools over streamable HTTP, for apps that take a URL instead of a command. Read-only, no sign-in.
- Claude (claude.ai and the desktop app): Settings → Connectors → Add custom connector, paste the URL.
- Claude Code:
claude mcp add --transport http archestack https://mcp.archestack.com/mcp - Any client:
{ "type": "http", "url": "https://mcp.archestack.com/mcp" }
It runs on Cloudflare's free Workers plan, so it allows 120 requests a minute per address and can run out of requests late in a busy day (UTC). It keeps no logs of your questions: privacy. For heavy use, run the npm package below.
Safety allowlist for admins
The hosted server also serves Archestack's safety checks as allowlists: MCP servers whose latest run passed every applicable check, pinned to the package version that was read, each with the official MCP Registry's record of that version.
- GitHub Copilot ("Registry only" policy): MCP Registry URL
https://mcp.archestack.com/registry(v0.1 API:/v0.1/servers,/v0.1/servers/{name}/versions/{version}). - Claude Code:
managed-mcp.jsonfor a fixed set, orallowedMcpServersfor managed settings. - The data:
/api/v1/allowlist.json. A check result is a fact about what was read on that date, not a guarantee.
Install
Needs Node.js 22 or newer. One click for Cursor or VS Code:
Claude Code
claude mcp add archestack -- npx -y @archestack/mcp
Claude Desktop: add this to claude_desktop_config.json (Settings → Developer → Edit Config), then restart the app.
{
"mcpServers": {
"archestack": { "command": "npx", "args": ["-y", "@archestack/mcp"] }
}
}
Cursor: the same mcpServers block in ~/.cursor/mcp.json, or in .cursor/mcp.json for one project.
VS Code without the button:
code --add-mcp '{"name":"archestack","command":"npx","args":["-y","@archestack/mcp"]}'
From source
git clone https://github.com/archestack/mcp.git archestack-mcp
cd archestack-mcp
npm ci && npm run build
Then point your client at node /full/path/to/archestack-mcp/dist/index.js instead of npx -y @archestack/mcp.
Tools
| Tool | What it does |
|---|---|
search_projects |
Finds projects by words and filters: list, category, license family, runs without a GPU, arm64 build, live demo |
get_project |
One project in full: score and its parts, place in its category, GitHub facts, health, links, review |
deploy_facts |
What it takes to run one project: Docker, arm64, GPU, RAM, outside services, port, its stated needs, upkeep |
top_in_category |
The ranking of one category, best first |
compare |
2 to 4 projects side by side |
check_repo |
Before you install a GitHub repo: listed or not, license, upkeep, safety checks passed and failed, higher picks |
alternatives_to |
Open-source picks for a paid product, such as Cursor or ChatGPT |
All seven are read-only. Things to ask:
- "Which vector database runs without a GPU?"
- "Open-source alternatives to Cursor"
- "Compare Open WebUI and LibreChat"
- "Top 5 coding agents with an arm64 build"
- "Check github.com/ruvnet/ruflo before I install it"
What comes back, shortened (search_projects with "vector database" and no_gpu, data of 2026-10-13):
{
"updated": "2026-10-13",
"total": 15,
"results": [
{
"name": "Milvus",
"place": 1,
"score": 81,
"stars": 46366,
"license": "Apache-2.0",
"gpu": "optional",
"arm64": true,
"tagline": "Distributed vector database with dense, sparse and hybrid search at scale",
"source_url": "https://archestack.com/best-of-ai/projects/milvus/",
"checked_at": "2026-10-13"
},
{ "name": "Meilisearch", "place": 2, "score": 75, "gpu": "none", "...": "..." }
]
}
How it works
- It talks to archestack.com and nothing else. The API is static JSON served with the site. The server sends nothing about you or your questions and has no telemetry.
- The npm server checks each file against the JSON Schema published next to it (/api/v1/schema/). If a file does not match, you get an error instead of a made-up answer. The hosted server skips this check to stay inside the free plan's CPU time; the tests run both against the same recorded files.
- Each request times out after 8 seconds, with two retries and backoff. The server keeps each file in memory for an hour; Archestack refreshes the data twice a day.
- Every project in an answer carries
source_url, its page on archestack.com, andchecked_at, the date its facts were checked on GitHub. ARCHESTACK_API_URLpoints the server at another copy of the API. The tests use it for a local one.
Data and license
The code is MIT. The data is CC BY 4.0 by Archestack: if you publish something built on it, link the project page (source_url).
Archestack checks every project on GitHub: stars, last commit, license, Docker files. How the score works: archestack.com/methodology/.
Development
npm ci
npm test # builds, then runs the server over stdio against recorded API answers
npm run fixtures # records fresh answers from archestack.com into test/fixtures
npx @modelcontextprotocol/inspector node dist/index.js # try the tools by hand
npx wrangler@4.141.0 dev # the hosted server on http://localhost:8787/mcp
src/worker.ts is the Cloudflare Worker entry (config in wrangler.jsonc); npm run deploy publishes it with CLOUDFLARE_API_TOKEN and CLOUDFLARE_ACCOUNT_ID set.
Bugs and ideas: open an issue.
Archestack MCP questions
How do I add Archestack MCP to Claude Code?
Run claude mcp add mcp -- npx -y @archestack/mcp in your terminal. Add --scope user to make it available in every project.
How do I add Archestack MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
What tools does Archestack MCP provide?
It exposes 7 tools, including search_projects, get_project, deploy_facts, top_in_category, compare.
What kind of information can I get about a specific project?
You can retrieve scores, GitHub facts, health metrics, deployment requirements like Docker or GPU needs, and reviews.