Search transcribed painting lessons. Results cite the exact lesson and Vimeo timestamp.
Search the mypaintingclub.com painting-lesson knowledge base. The knowledge base is built from transcribed Vimeo lessons covering topics such as colour mixing, brushwork, composition, value, edges, and painting techniques for oils and acrylics.
Given a natural-language question, the tool returns up to top_k relevant answers drawn from real lesson content. Each result includes:
answer: the lesson's explanation for that question
lesson_title: the name of the lesson
sales_page_url: the mypaintingclub.com page where members can watch
start_time_seconds / end_time_seconds: the exact clip in the video
vimeo_deep_link: a direct URL to that moment (e.g. https://vimeo.com/123456789#t=312s)
score: cosine distance (lower = more relevant; 0 = identical)
Use this tool whenever a member or agent asks a painting technique question that might be answered by a specific lesson.
| Name | Required | Description | Default |
|---|---|---|---|
| top_k | No | Maximum number of results to return (1–20). Default 5. | |
| question | Yes | Natural-language painting technique question to search for. Examples: 'how do I paint soft edges in oils', 'colour mixing for shadows', 'how to simplify a busy background'. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint and idempotentHint), the description details the output format, including the meaning of the score (cosine distance, lower = more relevant) and the inclusion of time-coded links. This adds significant behavioral context about the search results that the annotations do not convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded, beginning with the tool's purpose, followed by the output schema in a bulleted list, and ending with usage guidance. It's longer than the bare minimum, but every sentence adds useful information for an agent deciding whether and how to invoke the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with only two parameters and no siblings, the description covers the domain, the query type, the result structure, and the intended use case. The presence of an output schema further complements it, making the description sufficiently complete for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full descriptions for both parameters (question and top_k), including range and default. The description adds little beyond restating the natural-language question input and the top_k limit, so the schema carries the burden; the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a search over the mypaintingclub.com painting-lesson knowledge base, with a specific verb ('search') and resource. It also enumerates the types of content and the return structure, leaving no ambiguity about its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'Use this tool whenever a member or agent asks a painting technique question that might be answered by a specific lesson.' This is a clear trigger, and although there are no sibling tools to exclude, the guidance is unambiguous and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
search_painting_lessonsClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
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Only one tool exists, so there is no possibility of selecting the wrong tool. The tool's purpose is clearly scoped to searching painting lessons.
The single tool name 'search_painting_lessons' follows a clear verb_noun pattern and is descriptive. With only one tool, there are no inconsistencies to evaluate.
The server exposes only one tool, which feels thin for a general knowledge base. However, the scope is narrowly defined as search, so one tool is borderline acceptable.
The search tool covers the primary need of answering painting technique questions from lesson content. Minor gaps exist, such as the inability to browse all lessons or retrieve a specific lesson by ID, but these are workable around.