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Temsor API — Turkey & EU business data

by com.temsor

MCP Tool Surface Index

mcp_index

Searchable, dated archive of what every public MCP server actually exposes — tool definitions, daily change feed, and rug-pull detection.

The official MCP registry publishes a server’s name and address but not its tool surface; the only way to learn what a server exposes is to connect and call tools/list. This endpoint does that daily across every public remote server and keeps the result. Three things become answerable that the source cannot answer: tool-level search (the registry has none), uptime, and — the one that matters for security — what a tool’s description said yesterday. In MCP a tool description is part of the context handed to the model, so it is prompt text; if it changes after the user approved the server, the server has silently injected new instructions. Each indexed tool also carries a review score with the matched evidence, so the claim can be checked rather than trusted. Measurement boundary: only initialize and tools/list are ever called — never tools/call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSearch term (only `search`), e.g. `invoice`, `calendar`, `sql`.
daysNoWindow in days (`changes` and `server`).
toolNoTool name (only `tool` view).
typeNoEvent type filter (only `changes`), e.g. `tool_description_changed`.
viewNo`search`: search tool name/description · `changes`: change feed (the actual product) · `server`: per-day measurement history for one server · `tool`: definition history for one tool · `stats`: index-level totals.search
limitNo
serverNoRegistry server name, e.g. `com.temsor/api`. Required for `server`/`tool` views.
minRiskNoOnly tools whose review score is at or above this (only `search`).
severityNoOnly `changes`.

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden, and it delivers: it explicitly states the measurement boundary ('only initialize and tools/list are ever called — never tools/call'), explains the daily crawl, and discloses the security-relevant storage of historical descriptions. This gives a clear picture of the tool's safety profile.

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

Conciseness4/5

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

The description is longer than typical, but each sentence earns its place: the registered gap, the daily measurement process, the security motivation, and the tool-call boundary are all useful context. It is slightly discursive but well organized and front-loaded with the essential statement of what the tool is.

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 9-parameter, no-output-schema tool, the description provides a strong contextual frame: what data is collected, how often, what is never called, and why historical descriptions matter. It does not describe the output/return shape for the various views, but the schema's per-view descriptions help fill that gap.

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 schema covers 89% of parameters with descriptive comments, so the description does not need to re-explain each field. The description adds general context (search, changes, server history, review scores) but does not go beyond the schema in explaining parameter-specific behavior or required combinations per view.

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 and resource: a 'searchable, dated archive of what every public MCP server actually exposes.' It clearly distinguishes the tool from the unrelated sibling validation/lookup tools by defining its own niche as an index, change feed, and rug-pull detector.

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

Usage Guidelines4/5

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

The description identifies concrete use cases: tool-level search, uptime tracking, and security change detection. It explains when this endpoint is uniquely valuable ('the only way to learn what a server exposes'), but it does not explicitly state when not to use it or name alternative search/validation tools.

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

All Temsor API — Turkey & EU business data toolsInspect
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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., bic_validate vs vin_validate), but there is notable overlap: tr_validate bundles Turkish validations that are also covered individually by iban_validate and tin_validate. Also, lei_validate and lei_lookup are closely related but distinct enough. Overall, agents can usually pick the right tool, but a few pairs could confuse.

Naming Consistency4/5

Tool names are consistently snake_case with predominately verb_noun patterns (e.g., validate, lookup, screen, parse, build). Some nouns like mcp_index, model_archive, and series_history break the verb pattern but are still predictable. Minor deviations from the noun_verb form (tr_invoice_build, shipping_identify) don't cause confusion. Very readable and consistent overall.

Tool Count3/5

With 27 tools, the set is heavy, exceeding the typical 3–15 well-scoped range. However, the server covers a broad domain: international standards validation, Turkey-specific business data (fuel, labor, invoices, addresses), and even MCP/LLM model archives. The count is justifiable given the scope, but it stretches coherence and may overwhelm agents.

Completeness4/5

The tool surface is remarkably comprehensive for the stated Turkey & EU business data purpose: validators for most ID types, VAT, IBAN, phone, VIN, sanctions; plus Turkey-specific operations like invoice build/parse, labor calculations, fuel prices, business days, and address parsing. Minor gaps exist (e.g., no general exchange-rate conversion, no credit-note-specific builder), but agents can accomplish core workflows without dead ends.

Resources