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AI Tooling Capability Union

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AI Tooling Capability Union

AI Tooling Capability Union

One normalized dataset for everything an AI agent can call right now: the canonical MCP server registry AND the OpenRouter model catalog, merged under a shared capability taxonomy. Query across both layers by task or capability. Keyless, no proxy.

Pricing

from $0.30 / 1,000 result items

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Cynix Dev

Cynix Dev

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The "what can my agent call right now" feed. One actor that merges the canonical MCP server registry and the OpenRouter model catalog into a single normalized dataset under a shared capability taxonomy — so an agent (or a human) can ask one question and get the servers and the models that satisfy it, cross-layer.

This is the Tier-3 play: Tier 1 indexed the MCP registry with an agentic matcher; Tier 2 indexed OpenRouter models with change detection. The Union is the novel combination — a single queryable surface over both tool layers, plus a per-capability coverage index that tells an agent exactly what tool surface is available.

What it does

  1. Fetches both layers — MCP servers from registry.modelcontextprotocol.io (cursor-paginated, deduped by name) and models from openrouter.ai/api/v1/models (keyless JSON, 422+ models).
  2. Normalizes each into one record shape with a shared capabilities tag set: name, id, description, capabilities, transport, remote_url, context_length, prompt_price_per_mtok, reasoning, ref_url.
  3. Matches an optional plain-English taskQuery across both layers using the same intent-aware scoring — a vision model that can call a web-search tool surfaces both the model and the server.
  4. Emits a capability index — per capability tag, how many MCP servers vs models support it. One row that tells an agent exactly what tool surface is available right now.

Input example

{
"taskQuery": "a vision model that can call a web search tool",
"capabilities": [],
"includeMcp": true,
"includeModels": true,
"maxMcpServers": 300,
"minMatchScore": 15,
"capabilityIndex": true
}

Output example (match records, one per layer)

{
"kind": "match",
"layer": "mcp",
"name": "ai.exa/exa",
"id": "ai.exa/exa",
"description": "Search the web with embeddings. The Exa MCP server exposes web search as a tool.",
"capabilities": ["web", "code"],
"transport": "streamable-http",
"remote_url": "https://mcp.exa.ai/mcp",
"context_length": 0,
"prompt_price_per_mtok": 0,
"reasoning": false,
"match_score": 100,
"matched_on": ["web"],
"ref_url": "https://registry.modelcontextprotocol.io/ai.exa/exa"
}
{
"kind": "match",
"layer": "model",
"name": "Nex AGI: Nex-N2-Mini",
"id": "nex-agi/nex-n2-mini",
"description": "A multimodal reasoning model with image understanding.",
"capabilities": ["reasoning", "function_calling", "json_mode", "vision"],
"transport": "api",
"remote_url": "",
"context_length": 262144,
"prompt_price_per_mtok": 0.12,
"reasoning": true,
"match_score": 100,
"matched_on": ["vision"],
"ref_url": "https://openrouter.ai/models/nex-agi/nex-n2-mini"
}

Output example (capability index record):

{
"kind": "capability_index",
"layer": "index",
"name": "Capability coverage",
"description": "Union of 302 MCP servers and 422 models.",
"coverage": { "vision": { "mcp": 5, "model": 59 }, "web_search_model": { "mcp": 0, "model": 0 } }
}

A real run returned 302 MCP servers + 422 models merged, with 536 cross-layer task matches. The capability index showed vision: mcp=5, model=59.

How to use

  1. Open the Actor and paste the JSON input (or use the form fields).
  2. Set taskQuery to a cross-layer task, or leave it empty to return the full union.
  3. Use capabilities to hard-filter (AND), or includeMcp / includeModels to narrow a layer.
  4. Click Start. Records appear in the default dataset.

Source notes

OpenRouter's public API does not expose modality flags for most models (0/422 carry an image modality), so model vision/audio caps are derived from description text — the same way MCP server tags are. The shared taxonomy normalizes imagevision so a vision filter hits both layers. MCP pagination is cursor-based (?cursor=); ?offset= is ignored.

Pricing

Pay-per-event: a small per-run start fee plus a per-record item fee. Both sources are public keyless JSON — no proxy, no per-call API cost. See the Actor's pricing tab for the current rate.

Compliance

Reads only publicly published registry/model metadata. No personal data, no login, no platform ToS conflict.

Support

Found a bug or need a field added? Open an issue on the Actor's Issues tab.