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mcp-ai-briefing

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mcp-ai-briefing

AI Briefing MCP — Keep AI models current on industry developments

Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.

Tools

Tool

Description

get_briefing

Get the daily AI tools digest for a given date (default: today) — new MCP servers, APIs, SDKs, and frameworks released in the last 24 hours, with summaries and source URLs.

search_developments

Search for new tools, APIs, MCP servers, and frameworks by keyword (e.g., 'vector databases', 'Claude integrations'). Returns matching developments with descriptions and sources.

get_recent

Retrieve AI developments from the last N days (default 7), filterable by category (e.g., model_release, paper, mcp), source (e.g., arxiv, github), and importance (low/normal/high/breaking).

get_model_landscape

List AI model releases from the last N days (default 30). Returns model names, provider companies, release dates, feature summaries, and source URLs grouped by importance.

get_timeline

Get a chronological timeline of AI developments between two dates. Returns events ordered by date with descriptions for understanding a specific period.

get_ai_toolbelt

Get the latest available tools — Claude Code features, MCP servers, SDK updates, CLI tools, integrations. Returns new capabilities since your training cutoff.

get_ai_news

Get AI industry news — model releases, funding, acquisitions, policy changes, benchmarks. Returns news events with dates and summaries for industry context.

what_happened

Ask natural language questions about recent tools and developments (e.g., 'any new MCP servers this week', 'latest Claude tools'). Returns the most relevant developments.

Related MCP server: The Agent Times MCP Server

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "ai-briefing": {
      "url": "https://gateway.pipeworx.io/ai-briefing/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/ai-briefing/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1476+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Ai Briefing data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

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