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Point Topic — UK Broadband Market Reference

Server Details

Point Topic public MCP: UK broadband market reference data — ISPs, networks, links and standards.

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Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Available Tools

1 tool
database_tools_execute_queryQuery Public Ontology DataA
Read-onlyIdempotent
Inspect

Query Point Topic's public broadband ontology (ClickHouse) — read-only. Exposes the public reference tables (the visitor view): the entity graph of ISPs, network operators, networks, links, link standards and their relationships. Discover tables with SHOW TABLES FROM ontology; inspect columns with DESCRIBE TABLE . Licensed measurement data (footprints, premises, speeds, tariffs, forecasts, take-up, subscribers) is not queryable here and requires a Point Topic licence — denied queries return contact details. Only SELECT/WITH/SHOW/DESCRIBE/EXPLAIN allowed; returns CSV (large results are truncated at ~50k tokens with a leading notice — add LIMIT to keep results small).

ParametersJSON Schema
NameRequiredDescriptionDefault
ctxNo
sql_queryYesThe SQL query to execute. Only SELECT/WITH/SHOW/DESCRIBE/EXPLAIN allowed.

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.9/5.0
Behavior5/5

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

The annotations already mark the tool as read-only, idempotent, and non-destructive, and the description reinforces this while adding significant behavioral context: CSV return format, ~50k token truncation with a leading notice, LIMIT recommendation, and the behavior for denied queries. No contradiction with 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?

A single dense paragraph front-loads the core purpose and read-only guarantee, then flows logically through constraints, workflow, and output behavior. No filler; every sentence contributes actionable information.

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

Completeness5/5

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

Covers scope, exclusions, allowed SQL, table-discovery workflow, return format, truncation behavior, and safety posture. With an output schema present and no sibling tools, nothing critical is missing for correct invocation.

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 description adds meaning beyond the schema by showing valid SQL forms (SHOW TABLES FROM ontology, DESCRIBE TABLE) and giving result-handling guidance. The optional ctx parameter is not explained, but it is nullable/defaulted and not required, making this a minor gap rather than a blocking one.

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?

States a specific verb ('Query'), a concrete resource ('Point Topic's public broadband ontology' / ClickHouse), and a read-only scope. It clearly separates this tool from the generic execute_query name and tells the agent exactly what data is in scope.

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?

Provides explicit workflow guidance: discover tables with SHOW TABLES FROM ontology, inspect columns with DESCRIBE TABLE, and restrict queries to SELECT/WITH/SHOW/DESCRIBE/EXPLAIN. It also states when not to use the tool — licensed measurement data is excluded and denied queries return contact details.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool update
    • First observeddatabase_tools_execute_query

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TDQS

A4.8/5.0
Disambiguation5/5

There is only one tool, so there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as a read-only query executor for the ontology.

Naming Consistency5/5

With a single tool named database_tools_execute_query, there are no naming inconsistencies within the set. The name uses a clear verb_noun structure and effectively describes the action.

Tool Count4/5

One tool is slightly below the typical 3-15 range, but it is a general-purpose SQL query interface that can handle all necessary operations (SHOW, DESCRIBE, SELECT). This makes the single tool reasonable and well-scoped for the server's purpose.

Completeness4/5

The tool fully covers the public reference ontology with read-only query capabilities, including schema discovery via SHOW/DESCRIBE. The main gap is that licensed measurement data is intentionally excluded, which is a domain limitation rather than a missing tool function.

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