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Web search and extraction · MCP server

Crawdar MCP: MCP server, setup and security

Crawdar MCP is an open-source MCP server that lets an AI agent research business leads and inspect qualification evidence before exporting results. Its repository has 0 stars and its last commit is from September 7, 2026 and it is licensed under MIT.

Score
50/100
Adoption (stars) 0/40
Maintenance 25/30
Framework (licence, registry, official) 25/30
OfficialActively maintained

What Crawdar MCP does

According to its repository: “Evidence-backed business discovery and lead-list research: search by brief or criteria, inspect qualification evidence and exclusions, and export results.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Crawdar MCP is listed under Web search and extraction, a category of 159 servers in the directory, where it ranks #159 by stars.

Topics declared by the repository: ai-agents, business-research, lead-generation, n8n, postman.

Installing and connecting Crawdar MCP

No package or remote server is declared in the official MCP registry: you install it from source, following the repository README.

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: TypeScript.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Crawdar MCP. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on August 21, 2026, the eliottreich/crawdar-mcp repository has 0 stars and 0 forks, with 1 open issues. It has more stars than 4% of the servers in the directory. Last change 2 months ago.

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

WigoloWigolo : 5.5K5.5KExa MCP serverExa MCP server : 5.2K5.2KJobSpyJobSpy : 4.6K4.6KTolgeeTolgee : 4.1K4.1KArxiv MCP serverArxiv MCP server : 3.2K3.2KTrieveTrieve : 2.7K2.7KTavily MCPTavily MCP : 2.5K2.5KOpen webSearchOpen webSearch : 1.9K1.9KCrawdar MCPCrawdar MCP : 00
GitHub stars of the most followed servers in the category (log scale); Crawdar MCP in orange. Checked October 25, 2026.

Verdict

Crawdar MCP is a reasonable choice; check the points below before connecting it.

Strengths

  • Maintained by the service's own vendor
  • Active project: recent commit
  • Permissive licence (MIT)

Limitations

  • Few visible users
  • Install from source

Frequently asked questions

How do I install Crawdar MCP?

No package is declared in the MCP registry: clone the eliottreich/crawdar-mcp repository, follow its README, then declare the start command in your client's MCP configuration.

Is Crawdar MCP free?

The code is published under the MIT licence and can be used free of charge.

Is Crawdar MCP safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Yes: the awesome-mcp-servers list marks it as the service vendor's official implementation.

What are the alternatives to Crawdar MCP?

In the same category: Exa MCP server, Brave search MCP server, Arxiv MCP server, and JobSpy. Exa MCP server and Brave search MCP server score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score