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tensorfeed logo

tensorfeed

RipperMercs/tensorfeed
1 starsv1.11.0STDIORegistry activeMITUpdated 2026-06-24Community

Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

claude mcp add tensorfeed -- npx -y @tensorfeed/mcp-server

Summary

RipperMercs/tensorfeed MCP server](https://glama.ai/mcp/servers/RipperMercs/tensorfeed/badges/score.svg)](https://glama.ai/mcp/servers/RipperMercs/tensorfeed) πŸ“‡ ☁️ - Real-time AI industry intelligence MCP server.

Connect from your MCP client

One-click install

Add this server to your editor with a single click. Fill in any required credentials afterward.

Claude Code

Run this once and Claude Code registers the server for you:

claude mcp add tensorfeed -- npx -y @tensorfeed/mcp-server

Claude Desktop

Add this to claude_desktop_config.json under Settings β†’ Developer β†’ Edit Config:

{
  "mcpServers": {
    "tensorfeed": {
      "command": "npx",
      "args": [
        "-y",
        "@tensorfeed/mcp-server"
      ],
      "env": {
        "TENSORFEED_TOKEN": "<TENSORFEED_TOKEN>"
      }
    }
  }
}

Cursor

Add this to .cursor/mcp.json in your project (or ~/.cursor/mcp.json for all projects):

{
  "mcpServers": {
    "tensorfeed": {
      "command": "npx",
      "args": [
        "-y",
        "@tensorfeed/mcp-server"
      ],
      "env": {
        "TENSORFEED_TOKEN": "<TENSORFEED_TOKEN>"
      }
    }
  }
}

Cline and other MCP clients

Most MCP clients accept the standard mcpServers JSON block:

{
  "mcpServers": {
    "tensorfeed": {
      "command": "npx",
      "args": [
        "-y",
        "@tensorfeed/mcp-server"
      ],
      "env": {
        "TENSORFEED_TOKEN": "<TENSORFEED_TOKEN>"
      }
    }
  }
}

Codex CLI

Register the server with OpenAI's Codex CLI β€” run this once, or add the equivalent block to ~/.codex/config.toml:

codex mcp add tensorfeed --env TENSORFEED_TOKEN=<TENSORFEED_TOKEN> -- npx -y @tensorfeed/mcp-server

# or add to ~/.codex/config.toml:
[mcp_servers.tensorfeed]
command = "npx"
args = ["-y", "@tensorfeed/mcp-server"]
[mcp_servers.tensorfeed.env]
TENSORFEED_TOKEN = "<TENSORFEED_TOKEN>"

OpenClaw

OpenClaw reads MCP servers from the mcp.servers section of ~/.openclaw/openclaw.json (managed via `openclaw mcp add` or the mcporter skill):

{
  "mcp": {
    "servers": {
      "tensorfeed": {
        "command": "npx",
        "args": [
          "-y",
          "@tensorfeed/mcp-server"
        ],
        "env": {
          "TENSORFEED_TOKEN": "<TENSORFEED_TOKEN>"
        }
      }
    }
  }
}

Replace the <PLACEHOLDER> values with your own credentials β€” see the configuration table below.

Configuration

tensorfeed reads the following environment variable:

VariableRequired
TENSORFEED_TOKENOptional

README.md

TensorFeed.ai

![Site](https://tensorfeed.ai) ![MCP Server](https://github.com/RipperMercs/tensorfeed-mcp) ![HF Dataset](https://huggingface.co/datasets/tensorfeed/ai-ecosystem-daily) ![AFTA Certified](https://tensorfeed.ai/agent-fair-trade) ![x402](https://tensorfeed.ai/.well-known/x402.json) ![License: MIT](LICENSE)

Real-time AI ecosystem intelligence built for humans and AI agents. News from 36+ sources, live service status for every major LLM provider, model pricing and benchmark history, an AI agents directory, and a pay-per-call premium API settled in USDC on Base mainnet (no accounts, no API keys).

🌐 Site: https://tensorfeed.ai Β· πŸ“Š Sister site: terminalfeed.io Β· πŸ“¦ HF dataset: tensorfeed/ai-ecosystem-daily Β· πŸ€– MCP server: tensorfeed-mcp

Three things make this different

  1. Code-enforced fair trade for agents. TensorFeed is the reference implementation of the Agent Fair-Trade Agreement (AFTA). Every paid call returns no charge on 5xx, breaker, schema-fail, or stale data, plus an Ed25519-signed receipt your agent can verify offline. Most APIs promise this. We code it.
  1. Two networks already federated. TensorFeed.ai and TerminalFeed.io accept each other's bearer tokens via a server-to-server validate + commit rail. One token, two sites. Other publishers can self-adopt by publishing a conforming /.well-known/agent-fair-trade.json.
  1. x402 from day one. No subscription, no signup, no email-me-the-API-key. Send USDC on Base, get a token, agent uses it. Compatible with Stripe Link Agents (April 2026 release): same x402 protocol, different scheme.

Want to AFTA-ify your own API? afta-gateway is a drop-in Cloudflare Worker template. Fork, set 3 secrets, deploy. MIT, no protocol fee.

Drop-in MCP server

The fastest way to plug an AI agent into TensorFeed is the official MCP server. It works in Claude Desktop, Claude Code, Cursor, Cline, Continue, Zed, Goose, and anywhere else that takes a stdio MCP config.

// claude_desktop_config.json
{
  "mcpServers": {
    "tensorfeed": {
      "command": "npx",
      "args": ["-y", "@tensorfeed/mcp-server"]
    }
  }
}

Restart your client and ask: "What's happening in AI today?" or "Compare pricing between Claude Opus and GPT-4o."

The MCP server has its own dedicated repo: github.com/RipperMercs/tensorfeed-mcp ⭐ full tool catalog, premium config, and example queries live there.

Try the API in 30 seconds

# Free, no auth
curl -s https://tensorfeed.ai/api/news?limit=5 | jq '.articles[] | {title, source}'

# Real-time provider status
curl -s https://tensorfeed.ai/api/status | jq '.services[] | {name, status}'

# Live model pricing across every provider
curl -s https://tensorfeed.ai/api/agents/pricing | jq '.pricing[] | {model, input_per_1m, output_per_1m}'

For premium endpoints (routing, history series, news search, cost projection, webhook watches, etc), buy credits in USDC on Base at tensorfeed.ai/developers/agent-payments. 50 credits per dollar at base rate, volume tiers up to 40% off, 50-credit welcome bonus on a wallet's first payment.

What's in the box

| Surface | What it is | Where | |---------|-----------|-------| | Web dashboard | Next.js 14, dark/light mode, 60+ pages | src/, deployed to Cloudflare Pages | | API backend | Cloudflare Worker tensorfeed-api, 70+ endpoints, 14 paid | worker/, attached to tensorfeed.ai/api/* | | MCP server | 22 tools (8 free, 14 paid), npm @tensorfeed/mcp-server | tensorfeed-mcp repo (mirrored from mcp-server/) | | Python SDK | pip install tensorfeed, optional [web3] for one-call USDC | sdk/python/ | | JavaScript SDK | npm install tensorfeed | sdk/javascript/ | | HF dataset | 42 daily JSONL feeds, 08:00 UTC commit, inference-only license | tensorfeed/ai-ecosystem-daily | | Browser extension | TensorFeed AI Status (Chrome + Firefox): toolbar popup with live provider status + passive degradation badge | Chrome, Firefox |

Free public endpoints

/api/news                  /api/status                /api/models
/api/benchmarks            /api/incidents             /api/pricing
/api/agents/{activity,news,status,pricing,directory}
/api/podcasts              /api/trending-repos        /api/attention
/api/embodied-ai           /api/training-datasets     /api/mcp-servers
/api/mcp/registry/snapshot /api/probe/latest          /api/gpu/pricing
/api/benchmark-registry    /api/harnesses             /api/funding
/api/health, /api/ping, /api/meta, /api/cron-status

Paid endpoints (1 credit each, USDC on Base)

/api/premium/routing                          # smart model routing
/api/premium/news/search                      # full-text + filters
/api/premium/cost/projection                  # workload cost projection
/api/premium/whats-new                        # agent morning brief
/api/premium/compare/models                   # side-by-side comparison
/api/premium/providers/{name}                 # one-provider deep dive
/api/premium/agents/directory                 # enriched + sortable
/api/premium/watches                          # webhook watches + digest
/api/premium/history/{pricing,benchmarks,status}/series
/api/premium/{mcp/registry,probe,gpu/pricing,attention}/series

Full docs: tensorfeed.ai/developers Β· agent-payments flow Β· machine-readable: /llms.txt, /openapi.json, /.well-known/x402.json, /.well-known/agent-fair-trade.json.

Discovery surfaces

Star this repo ⭐

If TensorFeed is useful to you (or your agents), starring helps other builders find it. The MCP server repo is also begging for stars if you use that surface specifically.

Built with Claude

TensorFeed was built in collaboration with Claude (Anthropic). Specific systems Claude designed alongside: the agent payments rail, the active LLM probes, the GPU pricing aggregator, the OFAC sanctions screening pipeline, the routing engine, and the AFTA standard itself. Git log shows the build trail.

Stack

Next.js 14 (static export) Β· Cloudflare Pages + Workers + KV Β· Tailwind Β· JetBrains Mono + Inter Β· Resend (email) Β· Cloudflare Web Analytics Β· Vitest. MCP server is plain TypeScript on top of the official @modelcontextprotocol/sdk.

Development

npm install
npm run dev      # Next.js dev server at localhost:3000
npm run build    # Static export (runs prebuild: fetch-feeds + generate-llms-full)
npm run lint

Worker (from worker/):

npm install
npm test         # 318 vitest cases, all green
wrangler deploy

MCP server (from mcp-server/ or the standalone repo):

npm install
npm run build
npm start

License

MIT. See LICENSE. Premium API responses ship under an inference-only license (no model training); see tensorfeed.ai/agent-fair-trade for the full terms.

Contact

  • support@tensorfeed.ai
  • press@tensorfeed.ai
  • feedback@tensorfeed.ai
  • Bug reports: GitHub issues

A Pizza Robot Studios project.

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