INDIVIDUAL MCP TOOL

get_agent_opportunities

Get TensorFeed's daily scan of new repositories across the AI agent ecosystem (Anthropic, OpenAI, Microsoft, ModelContextProtocol, HuggingFace, LangChain, frontier labs) plus recent MCP/x402/skills keyword sweeps.

tensorfeed.ainone authenticationAvailability not checked

Input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

Parent endpoint

tensorfeed.ai

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.tensorfeed]
url = "https://mcp.tensorfeed.ai/mcp"
enabled = true

Claude Code

.mcp.json

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

Claude Desktop

Settings → Connectors → Add custom connector

Name: tensorfeed
Remote MCP URL: https://mcp.tensorfeed.ai/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

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

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

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

Generic MCP

Client-specific MCP configuration

{
  "name": "tensorfeed",
  "transport": "streamable-http",
  "url": "https://mcp.tensorfeed.ai/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

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