Skip to main content
Glama
Sign In
gramps-evidence-mcp

gramps-evidence-mcp

by ianderso
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_dna_matches

Read-only

List DNA matches recorded for a person, showing shared centiMorgans, largest segment, and known common ancestor to guide relationship estimates and flag open research.

Instructions

List the DNA matches recorded against a person.

Each match reports total shared centiMorgans and the largest single segment — the two figures a relationship estimate actually rests on — plus any common ancestor already identified.

DNA evidence works differently from documentary evidence. A match proves a biological relationship exists; it does not say which one. Shared cM constrains the possibilities and rarely resolves them, and it says nothing about the paper trail. unattributed_count is the useful number: matches with no common ancestor identified are the open research.

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": {
      "person": "<person>"
    },
    "name": "get_dna_matches"
  }
}

Input Schema

NameRequiredDescriptionDefault
personYesHandle or gramps_id of the tested person.
include_rawNoInclude the unparsed note text the segments came from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real value beyond that: it names the key returned figures (shared cM, largest segment, common ancestor) and flags `unattributed_count` as the field that identifies open research, which shapes how an agent interprets results. It still omits pagination/return-shape specifics.

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?

Purpose is front-loaded in the opening sentence and the structure (what it returns, then interpretive caveat) is easy to scan. The bolded DNA-evidence paragraph is a bit editorial for a two-parameter read tool, but it is short and each sentence carries a distinct idea.

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?

There is no output schema, so the description usefully compensates by enumerating the per-match fields and calling out `unattributed_count`. For a simple read-only list tool with fully documented params this is nearly complete; only pagination and error behavior are unspecified.

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 both `person` and `include_raw` are documented in the schema itself. The description does not add syntax, handle-format, or default behavior beyond what the schema states, so the baseline of 3 applies.

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 first sentence gives a specific verb and resource ('List the DNA matches recorded against a person'), and the following sentences clarify the per-match payload. It does not differentiate itself from close siblings such as add_dna_match, get_ydna, or parse_dna_segments, so an agent still has to infer the boundaries from names alone.

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 only implied: an agent can tell this returns matches for a tested person, but there is no explicit when-to-use guidance or routing to alternatives like get_ydna (Y-DNA) or parse_dna_segments. The bolded note explains how to interpret DNA evidence generally, not when to call this tool instead of a sibling.

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

Deploy Server

Other Tools