Yappy documentation
Server Details
Yappy macOS docs (yappy.biz): setup, permissions, LLM backends, troubleshooting.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
3 toolsget_documentation_pageRead a Yappy documentation pageARead-onlyIdempotentInspect
Fetch one full Yappy documentation page as markdown, by slug. Use this after search_documentation when an excerpt is not enough and you need the whole page — for example the complete configuration reference or the full privacy model.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Which page to fetch. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying the output format ('as markdown') and the scope ('one full ... page'). It does not mention error handling for invalid slugs, but with annotations present this is a minor gap.
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?
Two tightly written sentences. The first states the core action, resource, and output format; the second gives routing guidance and concrete examples. No wasted words or repetition of the schema.
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 one-parameter tool with full enum documentation, strong annotations, clear sibling routing, and an explicit statement of the markdown return format, no meaningful context is missing. The description is sufficient 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?
Schema description coverage is 100%: the schema describes 'slug' as 'Which page to fetch' and enumerates all valid values. The description mentions 'by slug' but adds no additional semantics beyond what the schema already provides. Baseline 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 names a specific verb ('Fetch'), a specific resource ('one full Yappy documentation page as markdown'), and the key mechanism ('by slug'). It also implicitly differentiates itself from search_documentation by emphasizing 'full page' and 'markdown' versus an excerpt.
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 this tool: 'after search_documentation when an excerpt is not enough and you need the whole page.' It even gives concrete examples, making the decision boundary clear relative to its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_documentation_pagesList Yappy documentation pagesARead-onlyIdempotentInspect
List every page in the Yappy documentation with its slug, title, and one-line summary, so you can pick the right one to read instead of guessing a slug.
| Name | Required | Description | Default |
|---|---|---|---|
| include_summaries | No | Include each page's one-line summary alongside its slug and title. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context beyond those annotations: it states that the tool returns every page and specifies the returned fields (slug, title, one-line summary). No contradictions exist.
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 a single sentence that front-loads the action and resource, then explains the purpose with a clear rationale. Every word earns its place, and there is no redundancy or filler.
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 simple, read-only listing tool with one optional parameter, the description is completely adequate. It names the output fields, explains why the tool exists, and the schema documents the parameter. No output schema is needed because the description already tells the agent what will be returned.
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 single parameter include_summaries is fully described in the schema with its default and meaning, so schema coverage is 100%. The description mentions 'one-line summary' but does not explain the include_summaries flag; however, the schema carries that burden. A 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 names a concrete verb ('List'), a specific resource ('every page in the Yappy documentation'), and the exact output fields (slug, title, one-line summary). This clearly differentiates it from siblings like get_documentation_page (fetch one page) and search_documentation (query pages), so an agent can correctly select it.
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 states the intended use case: to pick the right documentation page instead of guessing a slug. It does not explicitly mention when to prefer search_documentation or get_documentation_page, but the purpose is clear enough that an agent can infer the distinction from the sibling names and this description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_documentationSearch Yappy documentationARead-onlyIdempotentInspect
Full-text search across Yappy documentation and FAQ. Use this to answer how-to and troubleshooting questions: installing Yappy, granting macOS permissions, a hotkey that does nothing, choosing an LLM backend, configuration keys, personas, or exactly what stays on-device. Results carry an excerpt you can quote and a URL you can cite.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Narrow the search to documentation pages or FAQ entries. | |
| limit | No | How many results to return. | |
| query | Yes | What to search for, in plain words. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context by noting that results include an excerpt and a URL, and by framing the search as covering both documentation and FAQ.
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 front-loaded with the core function, then gives focused use cases, then states the result format. The list of example topics is long but relevant and helps an agent form queries.
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?
Despite having no output schema, the description explains return value components (excerpt and URL). Together with the schema defining the three parameters, an agent has enough context to select and invoke the tool correctly. Minor gaps like handling no results are not critical here.
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?
Schema coverage is 100%, so the baseline is 3. The description adds example query topics and mentions full-text search, but does not add significant semantics beyond what the schema already provides for `query`, `type`, and `limit`.
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?
Description states a specific verb ('search') and resource ('Yappy documentation and FAQ'), with full-text scope and concrete example topics. This clearly distinguishes it from siblings that get or list pages.
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?
Explicitly says to use the tool for how-to and troubleshooting questions and gives concrete examples such as installing Yappy and macOS permissions. It does not explicitly state when not to use it or name alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
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.
Control your server's listing on Glama, including description and metadata
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Feature your server to boost visibility and reach more users
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Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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The server is experiencing an outage
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Credentials required to access the server are missing or invalid
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TDQS
The three tools map cleanly to distinct actions: search finds relevant content, list gives an overview of all pages, and get fetches a specific page by slug. There is no meaningful overlap, and the descriptions even prescribe how the tools chain together.
All tool names follow a consistent verb_noun snake_case pattern: search_documentation, list_documentation_pages, get_documentation_page. The slight variation between 'documentation' and 'documentation_pages' is natural since search also covers the FAQ.
Three tools is an appropriate size for a documentation server focused on reading and searching. Each tool earns its place, and none is redundant.
For a documentation MCP server, this surface is complete: search handles how-to and troubleshooting, list supports discovery when no slug is known, and get provides the full page when excerpts are insufficient. There are no dead ends or obvious missing operations.