Giphy
Server Details
Giphy MCP — wraps Giphy API (public beta key, free)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-giphy
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.9/5 across 8 of 8 tools scored.
Most tools have clearly distinct purposes: ask_pipeworx is a natural language query, discover_tools is for tool discovery, the GIF tools are for GIF retrieval, and the memory tools are for key-value storage. However, ask_pipeworx's description mentions it 'picks the right tool', which could overlap with the agent's own tool selection logic, causing slight ambiguity.
The GIF tools use verb_noun (random_gif, search_gifs, trending_gifs), but the memory tools use bare verbs (forget, recall, remember), and there are two tools with 'pipeworx' in the name. This mix of naming conventions reduces consistency.
With 8 tools covering GIF search, memory management, and a natural language interface, the count is well-scoped. Each tool serves a distinct purpose without unnecessary redundancy.
For GIF retrieval, the server covers random, search, and trending, which is fairly complete. However, the memory tools are basic CRUD (create, read, delete but no update). The ask_pipeworx and discover_tools are unique but seem to serve a meta-purpose that could overlap with the agent's built-in capabilities.
Available Tools
8 toolsask_pipeworxAInspect
Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question or request in natural language |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It explains that the tool internally selects the best data source and fills arguments, which is a useful behavioral trait. However, it does not mention potential side effects, rate limits, or any constraints on what types of questions are supported. The description is honest but not fully comprehensive.
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 concise at three sentences plus examples. It front-loads the core purpose and then provides additional context and examples. It could be slightly more structured (e.g., a bullet list of examples), but overall it is efficient and informative.
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 simplicity (single required parameter, no output schema, no nested objects), the description provides sufficient context for an agent to decide to use it and how to invoke it. The examples clarify the expected input format. The description is complete enough for this tool's complexity.
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 has 100% coverage with a single parameter 'question' described as 'Your question or request in natural language'. The description adds value by elaborating that the question should be in plain English and provides examples. This enhances the schema's minimal description.
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 accepts natural language questions and returns answers from the best available data source. It distinguishes itself from siblings by explicitly noting that Pipeworx handles tool selection and argument filling, so the user doesn't need to browse other tools. This effectively differentiates it from the other tools listed.
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 explains when to use the tool: when you want to ask a question in plain English and get an answer without manually selecting tools or learning schemas. It provides examples of appropriate queries. However, it does not explicitly state when not to use it or mention alternatives, though the sibling tools are different enough (e.g., discover_tools, search_gifs) that 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.
discover_toolsAInspect
Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of tools to return (default 20, max 50) | |
| query | Yes | Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it returns 'the most relevant tools with names and descriptions,' but does not detail what 'most relevant' means (e.g., ranking algorithm), whether results are ordered, or any side effects. For a search tool, this is adequate but not exhaustive; a 3 is appropriate as it does not contradict any annotations (none 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 two sentences long, with no wasted words. The first sentence states the action, the second provides crucial when-to-use guidance. Every sentence earns its place, and the structure is front-loaded with the core purpose.
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 simplicity (2 parameters, no output schema, no nested objects), the description is fairly complete. It explains the tool's role as a discovery mechanism and provides usage context. However, it lacks details on output format or whether results are ranked, but with no output schema, the description could be more explicit. Still, for a search tool, it is nearly complete, hence a 4.
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 schema already documents both parameters. The description adds value by giving an example query format ('analyze housing market trends') which clarifies the intent of the 'query' parameter beyond the schema's description. However, the 'limit' parameter is not elaborated upon in the description; the schema already provides its default and max. With full schema coverage, the baseline is 3, and the added example raises it to 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 explicitly states the tool's purpose: 'Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions.' The verb 'search' and resource 'tool catalog' are specific, and it clearly distinguishes itself from siblings like ask_pipeworx or search_gifs by focusing on tool discovery.
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 clear when-to-use guidance: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This advises the agent to use it as an initial step before invoking specific tools, implying it is a routing or discovery tool. No alternatives are explicitly named, but the context makes its role unique among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetAInspect
Delete a stored memory by key.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states it deletes a memory, implying irreversibility, but lacks detail on confirmation, error handling, or impact on related data.
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?
Single sentence, zero waste, front-loaded with verb and resource.
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?
Simple tool with one required parameter, no output schema, no nested objects. Description is adequate for a straightforward deletion, but lacks detail on what happens upon success/failure.
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% (key parameter is documented in schema). Description adds 'stored memory' context but does not go beyond what schema already says about the key parameter.
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 action 'Delete' and the resource 'stored memory by key', distinguishing it from sibling tools like 'remember' (store) and 'recall' (retrieve).
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 on when to use this tool vs alternatives like 'recall' or 'remember'. It does not mention prerequisites or side effects.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_gifAInspect
Get a random GIF, optionally filtered by tag (e.g., "cats"). Returns title, URL, rating, and image URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Optional tag to filter by, e.g. "dogs" or "anime" |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description carries the burden. It correctly indicates the tool is non-destructive (read-only). However, it does not disclose rate limits, API key requirements, or behavior when no GIF matches the tag (e.g., returns empty or error).
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 two sentences, no wasted words. It front-loads the action and scope, then lists return fields. Every sentence adds value.
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 low complexity (1 optional param, no output schema, no nested objects), the description is sufficient: it explains the tool's action, optional filtering, and return fields. No gaps remain for basic usage.
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% (the only parameter 'tag' is described). The description adds context that the tag is optional and gives examples. This is clear and helpful, earning a score above baseline 3.
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 retrieves a single random GIF from Giphy with optional tag filtering. It also lists the return fields, making the purpose specific and distinguishable from siblings like search_gifs and trending_gifs.
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 does not explicitly state when to use this tool versus siblings (e.g., search_gifs for non-random results, trending_gifs for popular ones). Usage is implied as 'for a random GIF,' but no alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recallAInspect
Retrieve a previously stored memory by key, or list all stored memories (omit key). Use this to retrieve context you saved earlier in the session or in previous sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | Memory key to retrieve (omit to list all keys) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions retrieving context from earlier sessions, implying persistence, but does not disclose any potential side effects or limitations. With no annotations, the description could provide more behavioral details such as whether retrieval is destructive or if there are rate limits.
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 concise with two sentences, front-loading the main action and providing a usage tip. No unnecessary 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 simplicity of the tool (single optional parameter, no output schema), the description adequately covers its purpose and usage. It lacks details about return format or error handling, but for a simple retrieval tool, this is sufficient.
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 describes the 'key' parameter, and the description adds context that omitting the key lists all memories. This adds value beyond the schema's description.
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 retrieves a memory by key or lists all memories. It distinguishes itself from sibling tools like 'remember' and 'forget' by focusing on retrieval.
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 explains when to omit the key to list all memories, and when to provide a key for specific retrieval. It also mentions using it to retrieve context from earlier sessions, but does not explicitly say when not to use it or suggest alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rememberAInspect
Store a key-value pair in your session memory. Use this to save intermediate findings, user preferences, or context across tool calls. Authenticated users get persistent memory; anonymous sessions last 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key (e.g., "subject_property", "target_ticker", "user_preference") | |
| value | Yes | Value to store (any text — findings, addresses, preferences, notes) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses persistence behavior: authenticated users get persistent memory, anonymous sessions last 24 hours. This adds useful context beyond the basic schema.
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?
Three sentences, front-loaded with the core action, then usage guidance, then persistence details. 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 no output schema and simple parameters, the description covers purpose, usage, and behavior. It could mention idempotency or whether overwriting an existing key is allowed, but overall it's fairly 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 description coverage is 100%, so the description adds only marginal value by providing usage examples for keys. Baseline is 3, and the description does not significantly enhance parameter understanding.
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 verb 'Store' and the resource 'key-value pair in your session memory'. It distinguishes from siblings like 'forget' and 'recall' by specifying the action of saving, not retrieving or deleting.
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?
It explicitly states to use this for saving intermediate findings, user preferences, or context across tool calls. However, it does not mention when not to use it or alternatives, but the context is clear and practical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_gifsAInspect
Search Giphy for GIFs by keyword. Returns title, URL, rating, and multiple image sizes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results to return (1–25, default 10) | |
| query | Yes | Search query, e.g. "funny cats" or "celebration" |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It discloses return fields (title, URL, rating, image URLs), which adds behavioral transparency beyond the schema. However, it does not mention potential rate limits or authentication needs.
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 short sentences, no fluff, front-loaded with action and resource. Efficiently uses space.
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 no output schema and only 2 simple parameters, the description provides a good overview of what the tool returns. Could mention pagination or ordering, but not essential for a simple search.
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 baseline is 3. Description does not add extra meaning beyond schema, as the schema already describes query and limit parameters clearly.
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 clearly states it searches Giphy for GIFs matching a keyword or phrase, listing the specific return fields. It distinguishes itself from sibling tools like random_gif and trending_gifs.
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?
Description implies usage for searching GIFs by keyword, but does not explicitly state when to use this vs. sibling tools like random_gif or trending_gifs, nor are there alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trending_gifsAInspect
Get currently trending GIFs on Giphy. Returns title, URL, rating, and multiple image sizes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results to return (1–25, default 10) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states returns title, URL, rating, and image URLs, but does not disclose rate limits, whether this is a read-only operation, or data source (Giphy). However, 'trending' implies non-destructive, and the lack of annotations is not a contradiction.
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, concise and front-loaded. First sentence states purpose, second lists returned fields. No filler, each sentence adds value.
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 a simple tool with one optional parameter and no output schema, description adequately covers purpose and return fields. Slight gap in not mentioning that results are from Giphy API, but 'on Giphy' is mentioned.
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 has 100% coverage for the single 'limit' parameter, which is described in the schema. Description adds no extra meaning beyond the schema, so 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?
Description clearly states verb 'get', resource 'trending GIFs', and returns title, URL, rating, and image URLs. Distinguishes from sibling 'random_gif' and 'search_gifs' by specifying trending scope.
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 explicit when/when-not or alternative tools mentioned, but context signals show a single optional parameter, implying simple usage. Sibling names like 'random_gif' and 'search_gifs' suggest alternatives, but description doesn't differentiate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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