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memory_edge_add

Add typed graph edges to link a source node to another node or a GitHub issue, using relations depends_on, relates_to, supersedes, derived_from, tracks. Specify one target: node ID or GitHub reference.

Instructions

Add a typed graph edge from a source node to another node or a GitHub issue. Relations: depends_on (task DAG), relates_to (mind-map link), supersedes, derived_from, tracks (issue <- task). Give exactly ONE target: a target_node_id (with an optional target_repo_id for a cross-repo edge) or a full github ref (owner + repo + number).

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": {
      "source_node_id": "<source_node_id>",
      "relation": "<relation>"
    },
    "name": "memory_edge_add"
  }
}

Input Schema

Name	Required	Description	Default
`relation`	Yes
`github_repo`	No
`github_owner`	No
`github_number`	No
`source_node_id`	Yes
`target_node_id`	No
`target_repo_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.10.1Jul 9, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description adds some behavioral context: it adds an edge with a specific relation and target. But it does not disclose side effects, uniqueness constraints, permissions, or error conditions.

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 two sentences, front-loading the core action and then listing relations and target options concisely without extraneous words.

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?

For a 7-parameter tool with no output schema, the description covers the main inputs and target selection but lacks return value details, error handling, or edge cases. It is adequate but has gaps.

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

Parameters4/5

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

Schema description coverage is 0%, so the description compensates by explaining the relation enum and the target options (node vs. GitHub issue). It adds meaning beyond the schema's field types and requiredness.

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 tool adds a typed graph edge from a source node to a target (another node or GitHub issue), and lists the possible relations. This distinguishes it from siblings like memory_edge_remove or memory_edges.

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 explicitly says 'Give exactly ONE target' and explains the two options (target_node_id or GitHub fields), providing clear context. However, it does not explicitly state when not to use this tool or mention alternatives.

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