ProductBrain MCP Server

search

Find product plan nodes by meaning, returning ranked matches with ancestor paths. Use it first for any lookup instead of scanning all nodes by label.

Instructions

Semantic search over the ProductBrain plan. Returns nodes ranked by similarity with ancestor paths. Use this FIRST for any lookup — never scan all nodes by label.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "search"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	natural-language query
`projectId`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 18, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the return shape (nodes ranked by similarity, with ancestor paths), which is real added value, but says nothing about result limits, pagination, or whether projectId scoping affects ranking.

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

Conciseness5/5

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

Two short sentences, zero filler, with the capability statement front-loaded and the routing instruction second. Every clause earns its place.

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

Completeness3/5

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

For a two-parameter read tool with no annotations or output schema, the description covers capability and return shape adequately but leaves the projectId scoping parameter and any result-size behavior unexplained.

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

Parameters2/5

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

Schema coverage is only 50%. The description implies a natural-language query via 'semantic search,' matching the documented q parameter, but adds no format or length guidance and is silent on projectId, which is undocumented in both the schema and the description.

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?

States a specific verb and resource ('Semantic search over the ProductBrain plan') and immediately distinguishes itself from the graph-walking siblings by warning against scanning nodes by label. An agent can tell this apart from list_nodes or get_tree without opening any schema.

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

Usage Guidelines4/5

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

Explicitly prescribes priority ('Use this FIRST for any lookup') and an exclusion ('never scan all nodes by label'), which routes the agent away from list_nodes. It stops short of naming the alternative tool directly, so it is clear context rather than a fully specified when/when-not rule.

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