memory-bank-mcp

Overview Schema Source Related Servers Discussions Admin

graph_search

Search a knowledge graph for entities and observations using fuzzy matching on names and text, with optional neighborhood expansion.

Instructions

Search the knowledge graph for entities and observations matching a query. Supports fuzzy matching on names and observation text.

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": {
      "query": "<query>"
    },
    "name": "graph_search"
  }
}

Input Schema

Name	Required	Description
`storeId`	No	Optional store ID to target a specific registered store instead of the active one
`query`	Yes	Search query string
`limit`	No	Maximum number of results (default: 10)
`includeNeighborhood`	No	Whether to include related entities (default: false)
`neighborhoodDepth`	No	Depth of neighborhood expansion (1 or 2, default: 1)

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.3.0Apr 30, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations provided, so the description must carry the burden. It mentions 'fuzzy matching', which adds some transparency, but does not detail case sensitivity, result ordering, or performance implications.

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 focused sentences with no wasted words; the purpose is front-loaded, making it quick for an agent to parse.

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?

With no output schema and no annotations, the description should explain more about the result format or behavior. It mentions a limit but not the structure of results, leaving some gaps for an agent.

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 baseline is 3. The description does not add meaning beyond the schema; it only repeats the fuzzy matching aspect already implied by the query 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?

The description clearly states the action 'Search' and the resource 'knowledge graph', specifies it retrieves entities and observations, and mentions fuzzy matching, which differentiates it from mutation tools like graph_upsert_entity or graph_add_observation.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like search_memory_bank or other search tools. The description lacks context for choosing it, leaving the agent to infer from the name alone.

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