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Glama
pavelpikta

lampa-mcp-server

Guide to CUB cloud APIs in Lampa

guide_cub
Read-onlyIdempotent

Read source-based documentation on how Lampa talks to CUB. Use topics like catalog, endpoint, auth, models, sync, and timeline_hash to understand API paths, schemas, and auth flows.

Instructions

Document how Lampa talks to CUB from source — this makes no network calls of its own (pure snapshot read), and is not a substitute for cub.rip/developer. Unlike list_catalog topic=mirrors/socket, this is CUB-specific. topic=catalog lists REST paths (category/search filter the catalog only, no effect on other topics); endpoint requires path (e.g. bookmarks/dump) and ignores category/search; auth reads auth_focus only (device/add, headers, Permit, Premium, mirrors); models reads model only (bookmark/timeline/favorite shapes); sync takes no parameters and maps dump/changelog/WebSocket; timeline_hash reads example only and explains Utils.hash.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoFor topic=endpoint: path such as 'bookmarks/dump' or 'device/add'.
modelNoFor topic=models: which schema. Default all.
topicYescatalog=endpoint table; endpoint=one path; auth=login/headers; models=schemas; sync=dump/changelog; timeline_hash=hash algorithm.
searchNoFor topic=catalog: filter by path substring.
exampleNoFor topic=timeline_hash: worked example.
categoryNoFor topic=catalog: filter by API category. Default all.
auth_focusNoFor topic=auth: focus area. Default overview.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
markdownYesHuman-readable markdown report. Always present, including empty-result cases. Does not write files.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.8.0

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint; the description reinforces and expands this with 'pure snapshot read' and 'makes no network calls of its own', and documents per-topic ignore/require behavior that annotations cannot convey. No contradiction with annotations was found.

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?

At roughly 150 words it is dense, but each clause covers one of the six topic modes and front-loads the core purpose and safety. No filler; the semicolon-delimited topic map is the most efficient way to convey the matrix of valid parameter combinations.

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?

With six topics and seven parameters, the description enumerates every topic's valid inputs and ignored fields, plus the tool's relationship to external docs and related tools. Given an output schema exists, not describing return values is acceptable; nothing needed to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all 7 params, so baseline is 3, but the description adds high-value cross-parameter constraints: `endpoint` requires `path` and ignores `category`/`search`, `auth` reads only `auth_focus`, `sync` takes no parameters, and `timeline_hash` reads only `example`. These interdependencies are not inferable from individual property descriptions.

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 uses 'Document how Lampa talks to CUB from source' – a specific verb and resource – and immediately separates it from `list_catalog` topics and cub.rip/developer, making the tool's CUB-specific scope unmistakable. It clearly distinguishes this from sibling tools without needing to open the schema.

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?

It gives explicit when-not guidance ('not a substitute for cub.rip/developer') and contrasts with the sibling `list_catalog` topic=mirrors/socket, making alternative selection concrete. The per-topic parameter rules also tell the agent exactly which parameters to provide for each mode, reducing guesswork.

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