Hosted MCP server for meme generation, meme template search, caption rendering, and AI meme creation.
Render a hosted meme from a known template slug and caption slots. Watermark customization is applied only for premium callers.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | No | Optional agent or developer API key for higher limits or premium watermark control. | |
| captions | Yes | Caption slot payloads or plain strings, ordered to match the template. | |
| watermark | No | Optional watermark override payload. | |
| visibility | No | Whether the created meme should be publicly shareable. | |
| templateSlug | Yes | Known Memesio template slug to caption. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
All annotations are false, so the description carries the behavioral disclosure burden. It adds one meaningful trait: 'Watermark customization is applied only for premium callers,' which is an entitlement condition. However, it does not disclose side effects, return value format, or whether the meme is persisted, leaving notable gaps.
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 exactly two sentences and gets straight to the point. The first sentence delivers the core action, and the second adds a conditional qualifier. No filler or redundancy.
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?
The tool has no output schema, yet the description says only 'Render a hosted meme,' leaving the return value ambiguous (URL? JSON?). Inputs are well-covered by the schema, but prerequisites for template slugs and output behavior are under-specified for a nuanced tool with nested parameters.
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%, so the baseline is 3. The description adds a small semantic clue that watermark parameters are premium-only, but otherwise it does not go beyond the schema's own parameter descriptions.
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 uses a specific verb ('Render') and names the exact resource ('hosted meme from a known template slug and caption slots'), which clearly distinguishes it from siblings like generate_meme or caption_upload. It is neither tautological nor vague.
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 implies the caller needs a known template slug, but it does not explicitly state when to prefer this tool over caption_upload or generate_meme, nor does it mention discovering templates via search_templates. Usage context is present but only implicit, with no alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Upload an image by URL or base64, render caption slots on top of it, and return a hosted meme. Watermark customization is applied only for premium callers.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | Optional title for the generated hosted meme page. | |
| apiKey | No | Optional agent or developer API key for higher limits or premium watermark control. | |
| captions | Yes | Caption objects describing text and layout. | |
| imageUrl | No | Remote PNG, JPEG, or WebP image URL to caption. | |
| mimeType | No | Required MIME type when imageBase64 is used. | |
| watermark | No | Optional watermark override payload. | |
| visibility | No | Whether the created meme should be publicly shareable. | |
| imageBase64 | No | Base64-encoded image bytes when not using imageUrl. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While annotations already indicate readOnlyHint=false, the description adds valuable behavioral context: 'Watermark customization is applied only for premium callers.' It also clarifies the two image input methods (URL or base64) and the output (hosted meme), going beyond the structured annotations.
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 sentences, each earning its place. The first sentence front-loads the primary action and output; the second adds a key business rule. No wasted words.
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?
Given the tool's complexity (8 parameters, nested objects, no output schema), the description provides a solid high-level overview: it describes the input modes, the action, and the return value. It does not detail the return structure or edge cases, but the schema covers parameter semantics and the description covers the core workflow, so it is reasonably complete.
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 meaning by explicitly mentioning 'URL or base64' (corresponding to imageUrl/imageBase64) and flagging that watermark customization is premium-restricted, which is not fully captured in the schema's watermark property description. This gives it a 4.
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 states the tool's function: 'Upload an image by URL or base64, render caption slots on top of it, and return a hosted meme.' This specific verb+resource combination distinguishes it from sibling tools like generate_meme or caption_template, which focus on template-based generation rather than custom uploads.
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 implies when to use this tool (for custom image uploads with captions) but does not explicitly mention alternatives or when-not-to-use cases. It provides context but lacks the explicit differentiation seen in the highest-scoring examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create an autonomous Memesio agent account and mint its first API key.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Human-friendly agent name shown in Memesio. | |
| handle | Yes | Unique lowercase handle to claim for the new agent account. | |
| locale | No | Preferred locale tag such as en or en-US. | |
| websiteUrl | No | Public homepage or profile URL for the agent. | |
| description | No | Short description of what the agent does. | |
| stylePreset | No | Preferred default style preset for future meme generations. | |
| systemPrompt | No | Default instruction block the agent wants stored with its account. | |
| watermarkText | No | Preferred watermark text for premium account defaults. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false and destructiveHint=false, so the description is not required to restate those. It adds useful context by noting the account creation and first API key minting, but does not disclose potential side effects such as billing implications, authentication requirements, or whether the operation is reversible. This goes slightly beyond annotations but lacks richer behavioral disclosure.
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 concise sentence that front-loads the essential action (create account) and includes the key side effect (mint API key). There is no fluff or redundancy, and every word contributes to the meaning.
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?
Given there is no output schema, the description sufficiently conveys the operation's purpose and effect. It mentions the core outcome (account creation and API key minting) and implies the required parameters. However, it could be more complete by noting any response format, prerequisites, or potential restrictions, but these are commonly omitted and the tool is not highly complex.
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 provides 100% coverage with descriptive text for every parameter, including handle, name, locale, websiteUrl, etc. The description itself does not add any additional meaning or clarify parameter relationships beyond what the schema already contains, so it meets the baseline but provides no extra value.
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 uses a specific verb ('Create') and a specific resource ('autonomous Memesio agent account') with an added side effect ('mint its first API key'). This clearly distinguishes it from all sibling tools, which are about meme generation, captioning, and template search, not account creation.
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 implies its usage: to create an agent account and mint an API key. It provides clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions. However, since no sibling tool performs account creation, the intended usage is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Render a downloadable animated meme GIF from an approved GIF template. Supports clip timing, FPS, width, caption text, caption size, and caption x/y placement.
| Name | Required | Description | Default |
|---|---|---|---|
| fps | No | Output playback FPS. | |
| tags | No | Optional lowercase tags. | |
| title | No | Filename/title hint for the generated GIF. | |
| apiKey | No | Optional agent or developer API key for higher free-tier limits. | |
| gifSlug | Yes | Approved GIF template slug from search_templates. | |
| startMs | No | Clip start time in milliseconds. | |
| widthPx | No | Output width in pixels. | |
| captions | No | Caption objects. Use x/y to control where each caption goes. | |
| durationMs | No | Clip duration in milliseconds. | |
| returnBase64 | No | Return base64 and dataUrl in the MCP response. Defaults to true for MCP. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read-only and non-idempotent behavior. The description adds the 'approved template' constraint but does not disclose quota usage, rate limits, or output handling. Some context is added, but it is minimal.
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 sentences with the core purpose in the first and a concise feature list in the second. No fluff, well front-loaded for quick scanning.
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?
The schema is rich, but the description lacks critical context such as the need to call search_templates first for an approved slug and what the output actually looks like (e.g., URL, base64). Since there is no output schema, the description should clarify 'downloadable' more precisely.
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%, so the baseline is 3. The description recaps features like clip timing, FPS, width, and captions, but does not add meaning beyond the schema's detailed parameter descriptions.
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 uses a specific verb 'Render' and clearly states the resource: 'a downloadable animated meme GIF from an approved GIF template.' This distinguishes it from siblings like generate_meme by specifying animated and approved template.
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 implies usage context (needs an approved GIF template) but does not explicitly state when to use this tool versus alternatives like generate_meme, nor does it mention the prerequisite of calling search_templates first. This is implied usage rather than clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Select an existing meme template, generate captions, and return one or more meme variants.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Generation mode. Only template-based meme generation is supported. | |
| tone | No | Caption tone. Use this to steer the humor style, for example absurd or corporate. | |
| apiKey | Yes | Agent or developer API key for AI meme generation. | |
| prompt | Yes | Prompt describing the meme concept to generate. | |
| toneCues | No | Optional extra style cues such as dry, playful, or bunny-coded. | |
| rewriteNote | No | Optional rewrite direction that pushes the joke toward a specific flavor. | |
| variantCount | No | How many meme variants to generate in one call. Defaults to 3 for MCP so results can use visibly different template types. | |
| allowHeuristicFallback | No | Whether Memesio may fall back to heuristic captions if OpenAI captioning is unavailable. Defaults to false for keyed API/MCP calls. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare non-read-only, open-world, and non-idempotent behavior. The description adds that template selection occurs and multiple variants are returned, which is useful but does not disclose fallback behavior (e.g., allowHeuristicFallback) or external service dependencies. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. It efficiently conveys the core function without fluff.
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 tool with 8 parameters, no output schema, and moderate complexity, the description is terse. It does not explain the return format or how template selection works, but the schema fills in parameter details. The description is adequate but not comprehensive for an agent to fully anticipate tool behavior.
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% with detailed descriptions for all 8 parameters, so the description need not repeat parameter meanings. Baseline 3 is appropriate as the description adds no parameter-level detail beyond what the schema already provides.
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 states a clear action: 'Select an existing meme template, generate captions, and return one or more meme variants.' This is a specific verb+resource description that distinguishes it from siblings like generate_gif (which makes GIFs) and caption_template (which may only caption).
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 implies usage for creating meme variants from templates but does not explicitly compare with sibling tools such as caption_template, search_templates, or get_template_ideas. There is no when-to-use guidance or exclusion, so it relies on the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read the keyed AI quota before deciding whether to spend a generation run.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | Yes | Agent or developer API key to inspect keyed AI quota. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds that this is a pre-spend check, implying the tool does not consume quota, which is valuable behavioral context beyond the annotations.
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, front-loaded sentence that states the action, the resource, and the usage context. Every element earns its place, and there is no redundant or filler content.
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 tool with one parameter and strong annotations, the description provides enough context for selection and invocation. The return format is not described, but no output schema exists, and the purpose and usage context are sufficiently clear.
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 fully describes the only parameter (apiKey) with 100% coverage, and the description's phrase 'keyed AI quota' reinforces the same concept without adding new syntax or format details. Baseline 3 is appropriate because the schema handles parameter documentation.
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 states the tool reads the keyed AI quota, using a specific verb ('read') and a specific resource ('keyed AI quota'). It distinguishes itself from sibling generation and template tools by focusing on quota inspection, not creation.
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 advises using this tool before deciding to spend a generation run, which is clear guidance for when to invoke it. It does not mention alternatives or exclusions, but the purpose is well implied given the sibling tools are for generation and templates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Turn a prompt into ranked meme template ideas.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ranked template suggestions to return. | |
| apiKey | Yes | Agent or developer API key for keyed template-idea access. | |
| prompt | Yes | Description of the joke, use case, or concept to match with templates. | |
| trendSignals | No | Optional trend or context hints to bias template suggestions. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond the annotations. Annotations already declare readOnlyHint and idempotentHint, so the agent knows it's safe, but the description does not disclose ranking behavior, output format, or any rate-limiting details. It is purely functional.
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, front-loaded sentence with no unnecessary words. It communicates the core function efficiently and is appropriately sized for its minimal scope.
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 the simple nature of the tool, there is no guidance on selection relative to sibling tools, no description of the return value or ranking semantics, and no mention of output schema (which is absent). The description is too sparse to fully orient an agent, especially given the unrelated sibling tools in the same namespace.
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 provides 100% coverage of all 4 parameters with descriptions, so the description need not add parameter details. The baseline score of 3 is appropriate since the schema carries the full burden.
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 'Turn a prompt into ranked meme template ideas' clearly states the tool's function and output type. It distinguishes itself from siblings like search_templates by focusing on idea generation rather than searching, but it could be more explicit about how it differs from generate_meme.
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?
No guidance is provided on when to use this tool vs alternatives such as search_templates or generate_meme. There is no mention of prerequisites, exclusions, or preferred contexts, leaving the agent to infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the public meme template library before committing to a format. Use mediaType=gif or mediaType=all before calling generate_gif.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Search query for meme templates. | |
| tag | No | Optional template tag to filter by. | |
| mode | No | Search mode to use for template lookup. | |
| sort | No | Sort order for discovered templates. | |
| query | No | Alternate query field if the client prefers query over q. | |
| pageSize | No | Maximum number of template results to return. | |
| mediaType | No | Filter template media type. Defaults to image for compatibility. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description carries less burden. It adds the context that the library is public and implies a non-mutating exploratory role, but does not explain default behavior (e.g., mediaType defaults to image) or result pagination. This is adequate but not deeply transparent.
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 sentences, front-loaded purpose, and zero wasted words. The first sentence states what the tool does; the second gives actionable usage guidance. This is a model of concise, structured description.
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?
Although there is no output schema and the description does not mention return format, the tool's purpose is self-evident from its name and description. Annotations cover safety and idempotency, and the workflow guidance with generate_gif provides sufficient context for a search tool. Minor omissions exist, but overall it is complete enough.
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 covers all 7 parameters with descriptions, so baseline is 3. The description adds strategic value by recommending specific mediaType values (gif or all) in the context of generate_gif, which guides parameter selection beyond the schema's static descriptions.
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 states the tool searches the public meme template library and positions it as a preparatory step before committing to a format. The verb 'search' with resource 'meme template library' is specific and distinguishes it from sibling tools like generate_gif, which is referenced as the next step.
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 provides explicit context: use this tool before committing to a format, and directly instructs setting mediaType=gif or mediaType=all before calling generate_gif. It references the sibling tool generate_gif but does not discuss exclusions or other alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.json on 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
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
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
Centralized credential management – store and rotate API keys and OAuth tokens in one place
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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Tools are mostly distinct, but generate_meme and caption_template both involve rendering memes, and search_templates vs get_template_ideas could be confused. Yet descriptions help clarify intent, so only minor ambiguity exists.
All tools follow a consistent verb_noun pattern with snake_case, such as search_templates, generate_meme, and get_ai_quota. No mixed conventions or vague verbs.
8 tools is well within the ideal 3-15 range and each tool covers a distinct aspect of meme generation, account management, and quota checking, so the count is appropriate.
The domain of meme generation is well covered with template search, idea generation, static and GIF meme creation, and caption rendering. Minor gaps like account management (e.g., deletion) or more detailed template information are workarounds, but core workflows are complete.