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sovantica

engrava-mcp

by sovantica

list_edges

Read-only

Filter stored graph edges by edge type, knowledge source, or metadata values; returns full records and a count for memory inspection.

Instructions

List stored edges with optional filters. Filter by edge type, by knowledge source, and by edge metadata: metadata_equals takes a mapping of field name to a required value (exact match on every pair), and metadata_in takes a mapping of field name to a list of allowed values (the field must equal one of them). Metadata keys are simple field names and values are JSON scalars. Returns full edge records including their metadata, and a count.

Input Schema

NameRequiredDescriptionDefault
limitNo
sourceNo
edge_typeNo
metadata_inNo
metadata_equalsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A3.5/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read. The description adds real value by disclosing the return shape ('full edge records including their metadata, and a count'), but it omits ordering, pagination/truncation behavior, and what happens when limit is hit, which matter for a list tool capped at 5000.

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?

The purpose statement is front-loaded and the two metadata filters are each defined in a single clause. The sentences are dense but every one carries information; the only mild drag is repeating the return content that the output schema already covers.

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

Completeness4/5

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

For a read-only filtered-list tool with a full output schema, the description covers the non-obvious parts (metadata filter semantics) and the return content. The gaps are minor: no word on limit defaults/paging or result ordering, which an agent would need to page reliably.

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 0%, so the description carries the burden — and it does explain metadata_equals and metadata_in carefully, including exact-match-all-pairs vs any-of semantics and that values are JSON scalars, which the schema's anyOf does not make obvious. However, limit, source, and edge_type receive no explanation at all, leaving the most basic paging parameter undocumented.

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

Purpose4/5

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

The opening sentence states a specific verb and resource ('List stored edges') plus scope ('with optional filters'), and the following sentences enumerate the filterable dimensions. It never names or contrasts with the sibling get_edges, so an agent must infer the boundary between listing and fetching edges.

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

Usage Guidelines3/5

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

Usage is implied by the filter description (use it to browse edges narrowed by type, source, or metadata), but there is no explicit when-to-use/when-not guidance and no mention of when get_edges or search_memory would be the better choice. The reader must derive the selection rule from sibling names alone.

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