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overpass-mcp

overpass-mcp

by Rusty0508
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

raw_overpass_query

Execute raw Overpass QL queries to handle custom filters, output geometries, and statistics that other tools cannot express. Empty input is rejected.

Instructions

Execute a raw Overpass QL query.

Advanced escape hatch for queries the other tools cannot express (custom filters, out geom;, statistics, etc). Length-validated; empty input is rejected before any network call is made.

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": {
      "ql": "<ql>"
    },
    "name": "raw_overpass_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
qlYesRaw Overpass QL query

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully mentions length validation and that empty input is rejected before any network call, but it does not disclose potential risks of raw query execution, error behavior, rate limits, or response size implications.

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: three short sentences with no redundancy. The main purpose is front-loaded in the first sentence, and the remaining sentences add useful context about scope and validation.

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

Completeness4/5

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

For a raw query escape hatch, the description covers purpose, alternatives, examples, and validation, and an output schema exists so return values need not be explained. It is incomplete only in not addressing failure modes or operational limits, such as what happens when a query is invalid or exceeds server-side constraints.

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 schema already describes 'ql' as 'Raw Overpass QL query' with min/max lengths, giving full coverage. The description adds value by enumerating example query contents (custom filters, 'out geom;', statistics) and clarifying validation behavior, which goes slightly beyond the schema.

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 opens with a specific verb-resource pair: 'Execute a raw Overpass QL query.' It further distinguishes itself from sibling tools by labeling it an 'Advanced escape hatch' for queries 'the other tools cannot express' and gives concrete examples like custom filters and 'out geom;'.

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

Usage Guidelines5/5

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

The description explicitly says when to use this tool: for queries that other tools cannot express, such as custom filters, 'out geom;', or statistics. This provides clear guidance on usage vs. the sibling geospatial tools, even if it does not enumerate every exclusion.

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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