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PostGIS MCP Server

PostGIS MCP Server

by receptopalak
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

spatial-join

Perform spatial joins between two tables using specified geometry columns and join types such as intersects, within, contains, or touches. Ideal for analyzing spatial relationships in PostGIS databases via the MCP server.

Instructions

İki tablo arasında mekansal join işlemi yap

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": {
      "table1": "<table1>",
      "table2": "<table2>",
      "join_type": "<join_type>"
    },
    "name": "spatial-join"
  }
}

Input Schema

NameRequiredDescriptionDefault
geometry_column1NoTablo1 geometri kolonu (varsayılan: geom)
geometry_column2NoTablo2 geometri kolonu (varsayılan: geom)
join_typeYesJoin tipi
limitNoSonuç limiti (varsayılan: 100)
table1YesBirinci tablo adı
table2Yesİkinci tablo adı

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions a 'spatial join operation' but doesn't disclose behavioral traits like whether it modifies data, requires specific permissions, has rate limits, returns geometry columns, or handles large datasets. For a tool with 6 parameters and no annotations, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence in Turkish ('İki tablo arasında mekansal join işlemi yap'), which is appropriately concise. However, it lacks front-loading of critical details (e.g., purpose in English, key constraints) and could be more structured for clarity.

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?

Given no annotations, no output schema, and 6 parameters, the description is incomplete. It doesn't explain what the tool returns, how results are structured, or any behavioral context. For a spatial operation tool with complexity, this leaves significant gaps for an AI agent.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning about parameters beyond implying two tables are involved. Baseline 3 is appropriate when the schema does the heavy lifting.

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 the tool performs a 'spatial join operation between two tables' (verb+resource), which is specific and understandable. However, it doesn't differentiate from sibling tools like 'geometry-intersection' or 'find-nearby' that might have overlapping spatial functionality, preventing a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. With many spatial siblings (e.g., 'geometry-intersection', 'find-nearby'), there's no indication of when this spatial join is preferred or what specific problems it solves compared to other tools.

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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