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Snap Router — MCP server

Task-to-tool discovery for AI agents, pay-per-call in USDC on Base (x402), free tier, no signup.

Hosted API: https://trigeochiral.com — set it as SNAP_API.

Tool

Tool

What

snap_router

Your task → the ranked x402 / MCP tools that serve it, over the merged x402 Bazaar + MCP Registry catalog (16k+). One pass, ~200ms, no LLM call. $0.003

Related MCP server: NEX Agent Co. MCP Server

Why

Past ~2,000 tools, semantic retrieval beats keyword and beats long-context. Coinbase's Bazaar /ask is LLM-ranked (a model call on every task); 402index falls back to keyword-only when its embedding service times out. Snap Router has neither hole.

Install

pip install snap-router-mcp
claude mcp add snap-router --env SNAP_API=https://trigeochiral.com -- snap-router-mcp

or with uvx (no install):

claude mcp add snap-router --env SNAP_API=https://trigeochiral.com -- uvx snap-router-mcp

Optional: SNAP_XPAYMENT = a base64 x402 X-PAYMENT payload, to make paid calls past the free tier. Without it you get 25 free calls/day per IP.

Direct HTTP (no MCP)

curl -sX POST https://trigeochiral.com/v1/snap -H 'content-type: application/json' \
  -d '{"task":"check a base token for honeypot before trading","k":4}'

License

MIT

Available Tools

1 tool
snap_routerSnap Router — task to the right toolA
Read-onlyIdempotent

Tool/service DISCOVERY, not execution. Input: an agent task in plain words. Output: a ranked shortlist of x402 services and MCP tools from the merged x402 Bazaar + MCP Registry catalog (16k+ entries) that can do it, each with price and a 'works well with' hint. One vector pass, ~200ms, no LLM call, hybrid keyword-fill so nothing is missed. Call this FIRST, before loading candidate tools into context, whenever you do not already know which tool serves a task. Example task: 'check a Base token for a honeypot before trading'.

ParametersJSON Schema
NameRequiredDescriptionDefault
kNohow many results to return
taskYesthe task, in plain language
registriesNorestrict to these catalogs (default: both)
max_price_usdcNodrop results priced above this

Output Schema

ParametersJSON Schema
NameRequiredDescription
taskYes
picksYes
engineNo
works_well_withNo

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnly/idempotent/openWorld), the description discloses meaningful behavior: one vector pass, ~200ms, no LLM call, hybrid keyword-fill, and a ranked output with price plus a 'works well with' hint. These are decision-relevant traits — cost, latency, and mechanism — that the annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the essential 'discovery, not execution' distinction and reasonably tight, but phrases like 'hybrid keyword-fill so nothing is missed' and the trailing example lean promotional and could be trimmed without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the description still covers scope (16k+ entries, two catalogs), latency, cost profile, and call timing. Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so k, registries, and max_price_usdc are already documented in the schema. The description only restates that input is 'an agent task in plain words', adding no syntax, format, or defaulting detail beyond the schema, which is the baseline-3 case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise verb+resource — 'Tool/service DISCOVERY, not execution' over a merged x402 Bazaar + MCP Registry catalog — and explicitly contrasts the tool with execution tools. An agent can immediately tell this is a routing/search step, not a task performer.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit call condition: 'Call this FIRST, before loading candidate tools into context, whenever you do not already know which tool serves a task.' The negative case (when you already know the tool) is implied by that phrasing, and the supplied example task makes the intended invocation concrete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedsnap_router

TDQS

A4.4/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of misselection or overlap; its stated purpose (catalog discovery before loading tools) is unambiguous. An agent cannot confuse it with anything else in this server.

Naming Consistency5/5

The single tool follows a clean snake_case verb/resource-style name (snap_router) that matches the server name. There is no second convention to conflict with.

Tool Count3/5

A one-tool surface is inherently thin, even though a discovery router is arguably a single-purpose operation. The rubric treats 1-2 tools as borderline, and this sits right at that edge.

Completeness3/5

For a pure discovery role, the tool covers the core 'find candidates' operation, but the surface is a dead end: no way to fetch full details for a given service/tool ID, filter by price/category, or paginate the 16k-entry catalog. Agents can work around this by rerunning searches, but it is a notable gap.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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