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mcp-lnav-canbus

mcp-lnav-canbus

by baxtheman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

extract_can_frames

Filter CAN bus logs to retrieve specific frames based on ID, channel, or timestamp range.

Instructions

Extract specific CAN frames by ID, channel, or time range.

Args: can_id: CAN ID to filter (hex format, e.g., '0x123') channel: CAN channel number (0-based) start_time: Start timestamp end_time: End timestamp limit: Maximum frames to return (default: 1000) session_id: Session identifier

Returns: List of CAN frames

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": "extract_can_frames"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
can_idNo
channelNo
end_timeNo
session_idNo
start_timeNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context, such as 'Maximum frames to return' for limit and 'hex format' for can_id, but it does not explain timestamp formats, session_id semantics, or behavior when no filters are applied. This is a moderate effort.

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 well-structured docstring with a concise summary sentence, labeled Args section, and Returns section. It is appropriately sized with no unnecessary fluff, making it easy to scan.

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 tool has 6 optional parameters and an output schema, and the description gives enough to attempt a call. However, it leaves significant gaps: timestamp format is unspecified, session_id is unexplained, and there is no context about how filters combine or what happens with no filters. It is adequate but not complete.

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?

The Args section provides a description for every parameter, adding meaning beyond the schema which has no descriptions. It includes helpful details like hex format for can_id and default value for limit, though some descriptions are terse (e.g., 'Start timestamp' without format).

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 description clearly states 'Extract specific CAN frames by ID, channel, or time range,' which uses a specific verb and resource. However, it does not differentiate from the sibling tool 'query_can_messages', so it lacks explicit sibling distinction.

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?

The description implies usage when filtering by ID, channel, or time range, but it provides no explicit guidance on when to use this tool versus alternatives like 'query_can_messages'. There are no stated exclusions or alternative recommendations.

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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