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Waggle-mcp

Waggle-mcp

by Abhigyan-Shekhar
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

grep

Execute a query against an .abhi knowledge graph file, using a saved query ID or ad hoc text, to retrieve matching nodes.

Instructions

Execute a saved or ad hoc query against an .abhi file (waggle grep). Triggers the file's on_query event actions and returns matching nodes.

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": {
      "input_path": "<input_path>"
    },
    "name": "grep"
  }
}

Input Schema

NameRequiredDescriptionDefault
query_idNoOptional saved query id from the file.
input_pathYesPath to the .abhi file to query.
query_textNoOptional ad hoc query text to execute.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.17

TDQS

B3.2/5.0
Behavior3/5

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

Without annotations, the description partially compensates by noting it triggers on_query events and returns nodes. However, it doesn't clarify whether the operation is read-only or has side effects, nor the behavior when both query_id and query_text are provided.

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 that front-loads the main action. It is concise with no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks important details for effective use, such as behavior when both optional parameters are provided, return value format, or error conditions. Despite good schema coverage, the absence of output schema and annotations leaves gaps.

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 coverage is 100% and descriptions for each parameter are minimal but clear. The tool description adds no additional semantic meaning beyond what the schema provides, so a baseline score of 3 is appropriate.

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 it executes saved or ad hoc queries on .abhi files, specifying the action and resource. However, it doesn't explicitly distinguish from sibling tools like query_graph, which may have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, mutual exclusivity of parameters, or when to choose saved vs ad hoc queries.

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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