ph-civic-data-mcp

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One-call civic profile for a place

get_area_profile

Read-onlyIdempotent

Fetches a consolidated civic profile for any Philippine place—demographics, economy, hazards, weather—by resolving the location to a standard code. Reports per-block errors for multi-source data.

Instructions

One-call correlated civic profile for a Philippine location.

Resolves the place once to its PSA Standard Geographic Code, then composes demographics (population, poverty), economy (regional inflation, national labor), procurement activity, multi-hazard risk, and the short-range weather outlook — in a single agent turn instead of eight. Adds derived cross-source context (e.g. infrastructure notices per 100k residents) so the caller does not have to normalize raw counts itself. Examples:

get_area_profile("Cebu City") city-level demographics, hazard, weather get_area_profile("NCR") region-level, no province in the chain get_area_profile("Tacloban") city under a resolved province

On failure: each block (population, poverty, inflation, labor, hazard, weather, infra, resolve) gets its own status in blocks. A failed sibling appears there and in caveats, never as a silent null. The top-level upstream_error is true only when a block is genuinely unreachable, not when a sibling rejected an argument or returned a real empty answer.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`location`	Yes	Municipality, city, province, or region name. e.g. "Leyte", "Cebu City", "Davao Region", "NCR".

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.4.0May 22, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Annotations already state readOnly and idempotent, and the description further details failure behavior: per-block status, caveats for failed siblings, and the specific condition for upstream_error. This provides additional behavioral context beyond the annotations.

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 efficient and well-structured, including examples and failure handling without redundant words. Every sentence contributes valuable information.

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?

The description covers input expectations, usage examples, and error behavior, which is sufficient for an agent to invoke the tool correctly. It does not enumerate the exact output structure but mentions the block layout, which is adequate for a composite tool of this nature.

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?

The input schema fully describes the 'location' parameter with examples for municipalities, cities, provinces, and regions. The description does not add extra semantic detail beyond the schema, so the baseline of 3 applies.

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 clearly states the tool provides a one-call civic profile for a Philippine location, specifying the scope and giving concrete examples. It implicitly distinguishes itself from specialized siblings by emphasizing aggregation of multiple data types into a single result.

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 mentions consolidating eight data types in one call, suggesting use over multiple specialized tools, but does not provide explicit when-to-use guidance or alternatives. Examples show usage but no clear directive on when to prefer this tool over siblings.

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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