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dynamic-feed

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Supplies live LLM pricing, MCP registry, service status, and AI news.

MCP ServerAI & KnowledgeRemote (streamable-http)
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Updated 2026-06-16

What is the dynamic-feed MCP server?

Dynamic-feed addresses knowledge cutoffs by providing continuously updated information on AI-related topics. It aggregates pricing from major LLM providers, tracks registered MCP servers, monitors service availability, and surfaces relevant news headlines.

Users connect their AI clients to this remote endpoint to query fresh data without requiring local installation or additional API keys beyond the transport connection itself.

Install & connect

Add this to your MCP client config. Pick your client below and copy.

{
  "mcpServers": {
    "dynamic-feed": {
      "url": "https://dynamicfeed.ai/mcp"
    }
  }
}

Example prompts

Once connected, try asking your AI client:

What is the current price per million tokens for Claude 3.5 Sonnet?
List recently added MCP servers in the ai category
Show the latest AI news headlines from the past 24 hours
Is the OpenAI API currently reporting any outages?

Security & permissions

Requires remote streamable-http connection to the dynamic-feed server; no local filesystem access or stored secrets are needed.

What you can do with dynamic-feed

Check live model costs

Query current pricing for GPT-4o, Claude 3.5, or Gemini to compare expenses before running large workloads.

Discover available MCP servers

Search the registry for new or updated MCP servers by category, transport type, or capabilities.

Monitor AI service status

Retrieve real-time health information for popular AI APIs and news about recent incidents or releases.

How to use dynamic-feed

  1. 1Obtain the streamable-http endpoint URL for dynamic-feed.
  2. 2Configure your MCP client with the remote server address.
  3. 3Establish the connection using the streamable-http transport.
  4. 4Test by asking your AI client for current LLM pricing data.
  5. 5Monitor responses for fresh registry or news updates.

dynamic-feed: pros & cons

Pros

  • +Provides data AI models cannot access natively
  • +Covers multiple high-value topics in one server
  • +Remote access requires minimal client setup
  • +Keeps information current without retraining

Cons

  • Depends on external server availability
  • No tools documented in available description
  • Limited to the four data domains listed
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Frequently asked questions

No API keys are mentioned; only the streamable-http endpoint is needed.

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