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Understand-Anything MCP Server

Understand-Anything MCP Server

by VIethoangnguyenle
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_graph_metadata

Retrieve structured JSON metadata for a project's knowledge graph, including node/edge counts and repository state. Use it for machine-readable graph status.

Instructions

Structured JSON snapshot of a project's graph state: identity, node/edge counts, graph commit, repository HEAD and freshness. Machine counterpart of get_graph_stats — parse it instead of the text output.

Args: project: Project name. Leave empty if only one project is loaded.

Returns: JSON string: {"ok": true, ...metadata} or {"ok": false, "error": {"code", "message", "remediation"}}.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_graph_metadata"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the output format (JSON string with ok/error structure), including error code/message/remediation, and explains project handling. The 'snapshot' wording implies a read-only operation, though it does not explicitly state 'read-only' or side-effect-free. This is a minor gap but the description otherwise provides solid behavioral context.

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?

The description is well-structured with a concise opening sentence, an Args section, and a Returns section. Every sentence adds value, with no redundancy.

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?

For a tool with a single optional parameter and an output schema available, the description covers the return format, error handling, and parameter behavior. It even provides a usage alternative. The tool's simplicity is fully matched by the description's completeness.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates by explaining the project parameter: 'Project name. Leave empty if only one project is loaded.' This adds meaning beyond the bare schema definition.

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?

Description states 'Structured JSON snapshot of a project's graph state' and lists specific contents: identity, node/edge counts, graph commit, repository HEAD, freshness. It also differentiates from the sibling get_graph_stats by calling it the 'Machine counterpart' and saying 'parse it instead of the text output.'

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?

Explicitly names get_graph_stats as the alternative and instructs to use this tool for machine parsing instead of text output. Also provides project parameter usage guidance: 'Leave empty if only one project is loaded.'

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

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