TensorFeed MCP MCP server

An official MCP server providing AI news, model pricing, service status, and machine-payable premium tools. It supports 27 tools including SEC EDGAR, openFDA, and CVE data, with premium features like route_verdict payable via USDC on Base using the x402 standard.

Endpoint and access

No sign-in: your client connects and lists tools immediately, with no account or key.

No sign-inEndpoint checked 2026-10-05Operated by TensorFeed

MCP endpoint (Streamable HTTP)

https://mcp.tensorfeed.ai/mcp

Vendor documentation

What you can do with it

Lookup SEC company ticker information
Check AI model pricing and service status
Retrieve AI news and research papers
Execute premium model routing verdicts

Tools advertised by the last live check:

get_news_articles
get_status_summary
get_models
get_cve_record
get_kev_catalog
get_epss_score
get_osv_advisory_for_package
get_osv_advisory_by_id
check_ai_supply_chain_risk
check_agent_reputation
search_agent_directory
get_verified_hireable_status
list_directory_skills
check_free_tier_status
submit_wantlist_item
register_free_watch
search_sec_edgar
get_sec_submissions
lookup_sec_company_ticker
query_fda
get_eia_series
get_research_papers
get_weather_alerts
get_recent_earthquakes
get_agent_opportunities
route_verdict
whats_new

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers a Streamable HTTP server. Use --scope project to write .mcp.json for the repo.

Claude Code configuration

claude mcp add --transport http tensorfeed-mcp https://mcp.tensorfeed.ai/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).

Codex configuration

codex mcp add tensorfeed-mcp --url https://mcp.tensorfeed.ai/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable tensorfeed-mcp in your MCP settings.

Cursor configuration

{
  "mcpServers": {
    "tensorfeed-mcp": {
      "url": "https://mcp.tensorfeed.ai/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure). The type must be streamableHttp for a remote HTTP server.

Cline configuration

{
  "mcpServers": {
    "tensorfeed-mcp": {
      "type": "streamableHttp",
      "url": "https://mcp.tensorfeed.ai/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start tensorfeed-mcp and inspect its tools.

VS Code configuration

{
  "servers": {
    "tensorfeed-mcp": {
      "type": "http",
      "url": "https://mcp.tensorfeed.ai/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.

Gemini CLI configuration

gemini mcp add --transport http tensorfeed-mcp https://mcp.tensorfeed.ai/mcp

Claude Desktop

Merge this into claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\), then restart Claude Desktop.

Claude Desktop configuration

{
  "mcpServers": {
    "tensorfeed-mcp": {
      "url": "https://mcp.tensorfeed.ai/mcp"
    }
  }
}

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.

Windsurf configuration

{
  "mcpServers": {
    "tensorfeed-mcp": {
      "serverUrl": "https://mcp.tensorfeed.ai/mcp"
    }
  }
}

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