lnkz-mcp

Build the conversation graph

build_context_graph

Read-only

Constructs a knowledge graph from stored conversations to reveal key decisions, open questions, shared topics, and contradictions. Identifies dependencies and isolated discussions for deeper insights.

Instructions

Builds a graph over the stored conversations: nodes for conversations, decisions, open questions and shared topics, and edges for lineage, shared subject matter, near duplicates and contradictions. Answers the questions search cannot: what this corpus knows, which decisions everything else leans on, and which conversations stand alone. Every edge carries the reason it exists.

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": "build_context_graph"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`maxTopics`	No
`conflictThreshold`	No
`duplicateThreshold`	No
`minTopicConversations`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Sep 7, 2026

TDQS

A3.8/5.0

Behavior4/5

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

The description explains what the graph contains and the kind of analysis it supports, going beyond the simple readOnlyHint annotation. It does not mention side effects, but it also does not contradict the read-only annotation.

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 concise, front-loaded with the core action, and uses only two sentences. It avoids unnecessary detail while still conveying the tool's purpose and outputs.

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?

The description explains the graph's node/edge types and high-level value, but it lacks any explanation of the five parameters and does not describe the return format. Since there is no output schema, this leaves some gaps for an agent deciding how to invoke the tool.

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

Parameters1/5

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

The schema has five parameters with 0% description coverage, and the description does not mention any of them. An agent cannot infer the meaning or effect of limit, maxTopics, conflictThreshold, duplicateThreshold, or minTopicConversations from this 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 a specific action ('Builds a graph') and a specific resource ('stored conversations'), and distinguishes it from search by noting it answers questions search cannot. It differentiates well from sibling tools like search_conversations and find_conflicts.

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?

The description implies when to use it: when corpus-level relationships and insights are needed, and contrasts with search. It does not explicitly name sibling alternatives such as find_conflicts or find_duplicates, but the intent is reasonably clear.

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