agenticfeed-mcp

endpoint

https://agenticfeed.ai/mcp

door code

0fe5b2fd2a55b113

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is agenticfeed-mcp live?

Yes — it answered the hub's last check (checked 3h ago). It answered 100% of checks over the last 30 days.

Is agenticfeed-mcp free to use?

Yes — the hub reached it with no key and no payment.

What tools does agenticfeed-mcp have?

4 tools: list_products, get_product, find_merchant, search_products.

Is agenticfeed-mcp safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• list_products reads unknown 25h ago

  List a merchant's in-stock products (product_id, title, price, availability, url). Call after find_merchant to see the catalogue, then get_product for full detail. For a specific shopper need, prefer search_products.

  mcp-tool

  1234567891011121314151617

  {
    "type": "object",
    "required": [
      "merchant"
    ],
    "properties": {
      "limit": {
        "type": "integer",
        "description": "Max products to return (default 50, max 200)."
      },
      "merchant": {
        "type": "string",
        "description": "Agenticfeed merchant ID (customer GUID), e.g. \"a9a8378c94\"."
      }
    },
    "additionalProperties": false
  }

  arguments 17 lines copy
• get_product reads unknown 7h ago

  Get full detail for a single product by merchant_id and product_id: name, price, currency, availability, image, and the buyer questions, problems, and use cases it maps to. Returns a schema.org Product.

  mcp-tool

  123456789101112131415161718

  {
    "type": "object",
    "required": [
      "merchant",
      "product_id"
    ],
    "properties": {
      "merchant": {
        "type": "string",
        "description": "Agenticfeed merchant ID (customer GUID), e.g. \"a9a8378c94\"."
      },
      "product_id": {
        "type": "string",
        "description": "Product ID (product GUID) within that merchant's catalog."
      }
    },
    "additionalProperties": false
  }

  arguments 18 lines copy
• find_merchant reads unknown 7h ago

  Resolve a merchant's website domain to their Agenticfeed merchant ID and confirm they publish an Agentic Feed. Call this first when you only know a store's domain; use the returned merchant_id with get_product or the discovery feeds.

  mcp-tool

  12345678910111213

  {
    "type": "object",
    "required": [
      "domain"
    ],
    "properties": {
      "domain": {
        "type": "string",
        "description": "Merchant website domain or URL, e.g. \"boardgameextras.co.uk\"."
      }
    },
    "additionalProperties": false
  }

  arguments 13 lines copy
• search_products reads unknown 7h ago

  Find a merchant's products that match a shopper's need, question, problem, or use case. Pass the buyer intent in natural language (e.g. "a light strategy game for 4 players under thirty pounds"); returns ranked in-stock products with the reason each fits, drawn from Agenticfeed's intent mapping (questions, problems, use cases). Call find_merchant first to get the merchant ID.

  mcp-tool

  12345678910111213141516171819202122

  {
    "type": "object",
    "required": [
      "merchant",
      "query"
    ],
    "properties": {
      "limit": {
        "type": "integer",
        "description": "Max results to return (default 5, max 10)."
      },
      "query": {
        "type": "string",
        "description": "The shopper's need, in natural language."
      },
      "merchant": {
        "type": "string",
        "description": "Agenticfeed merchant ID (customer GUID)."
      }
    },
    "additionalProperties": false
  }

  arguments 22 lines copy

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.