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engineering-knowledge-mcp

engineering-knowledge-mcp

by niallr12
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Capture knowledge (low-friction inbox)

capture_knowledge

Save a durable engineering fact or convention in plain language when asked to remember it. Appends a timestamped entry to the knowledge inbox for later triage, so no need to know where it belongs.

Instructions

Low-friction capture of a durable engineering fact or convention, e.g. 'When testing the modelling API locally, X must be set to Y.' Appends a timestamped entry to inbox/knowledge-inbox.md for later triage into knowledge/. Does not require knowing where the information belongs. Use when the user explicitly asks to remember, capture, or add durable engineering knowledge.

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": {
      "content": "<content>"
    },
    "name": "capture_knowledge"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYesThe knowledge to capture, in plain language
suggestedTopicNoOptional hint about where this might eventually belong

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure, and it succeeds: it states that it appends a timestamped entry to a specific file (inbox/knowledge-inbox.md) and that the entry is for later triage into knowledge/. It also clarifies that it does not require knowing where the information belongs, setting correct expectations. It could mention potential effects (e.g., file creation or append behavior) but the essential behavior is transparent.

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 a single, well-structured sentence followed by an example and a usage directive. It front-loads the core purpose, provides a concrete illustration, and adds the usage trigger without any filler. Every element earns its place, and the whole fits comfortably in a readable length.

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 only two parameters, one required, no output schema, and no nested structures, the description is fully sufficient. It covers what the tool does, where it writes, when to use it, and the key benefit (low friction). Nothing an agent needs to correctly invoke this tool is missing.

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?

Although the schema already documents both parameters at 100% coverage, the description adds meaningful semantic context. It explains that content is a durable engineering fact or convention, gives an example, and clarifies that suggestedTopic is optional because the tool does not require knowing the target location. This goes beyond mere schema repetition and helps an agent understand how both fields interact.

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 states a specific verb ('capture'), a target resource (durable engineering knowledge appended to inbox/knowledge-inbox.md), and a clear distinction from direct knowledge creation. It includes a concrete example that helps an agent immediately recognize what counts as appropriate input, and the sibling list (create_knowledge) reinforces the uniqueness of this tool as an inbox capture.

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?

Provides explicit guidance on when to use the tool: 'Use when the user explicitly asks to remember, capture, or add durable engineering knowledge.' It also explains the benefit ('Does not require knowing where the information belongs'), which implicitly signals that create_knowledge is the alternative when topic placement is known. However, it does not explicitly list when-not-to-use conditions or name sibling alternatives, so it falls just short of a 5.

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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