Pipedrive
Server Details
Pipedrive MCP Pack — wraps the Pipedrive REST API v1
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-pipedrive
- GitHub Stars
- 0
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.7/5 across 13 of 13 tools scored. Lowest: 2.9/5.
Tools are mostly distinct with clear descriptions. 'ask_pipeworx' could theoretically subsume 'compare_entities' and 'resolve_entity', but their specific purposes (comparison and ID resolution) are well-defined. Memory tools are separate. Overall, an agent can distinguish them.
Naming conventions are mixed: some use verb_noun (ask_pipeworx, compare_entities), some use server prefix (pipedrive_get_deal, pipeworx_feedback), and some are standalone verbs (forget, recall, remember). No consistent pattern across the set.
13 tools is reasonable for a combined CRM and data query server. The count is not excessive, though the inclusion of memory and discovery tools adds breadth beyond the core CRM scope.
Pipedrive tools only cover reading (get, list, search) but miss create, update, and delete operations, which are essential for CRM management. Pipeworx tools cover queries and resolution but lack updates. Memory tools are complete for their domain.
Available Tools
13 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?
No annotations are provided, so description carries full burden. Describes high-level behavior (picks tool, fills arguments, returns result) but lacks details on potential limitations, such as what happens if no data source matches, error handling, or rate limits. Adequate but not 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?
Description is concise (3 sentences) and front-loaded with the core purpose. Examples add useful context but could be considered slightly redundant for a simple tool. No wasted words, though could be trimmed without losing 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 the tool has a single parameter and no output schema, the description is sufficiently complete for the agent to understand its purpose and how to use it. Provides enough context about delegation behavior and examples. Minor gap: does not explain what 'best available data source' means or if there are any prerequisites.
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?
Only one parameter (question) with 100% schema coverage. Schema already describes 'Your question or request in natural language'. Description adds value by explaining that the question should be in plain English and provides examples, which clarifies the expected format beyond the schema 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?
Description clearly states verb+resource: 'Ask a question... and get an answer from the best available data source.' It explicitly distinguishes from siblings by highlighting that Pipeworx handles tool selection and argument filling, so the agent does not need to browse other tools or schemas.
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?
Provides clear context for when to use: when you have a plain English question and want the system to pick the right tool. Does not explicitly state when not to use or name alternative tools, but examples and description imply it handles broad queries that would otherwise require navigating multiple tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_entitiesAInspect
Compare 2–5 entities side by side in one call. type="company": revenue, net income, cash, long-term debt from SEC EDGAR. type="drug": adverse-event report count, FDA approval count, active trial count. Returns paired data + pipeworx:// resource URIs. Replaces 8–15 sequential agent calls.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Entity type: "company" or "drug". | |
| values | Yes | For company: 2–5 tickers/CIKs (e.g., ["AAPL","MSFT"]). For drug: 2–5 names (e.g., ["ozempic","mounjaro"]). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions data sources (SEC EDGAR, FDA) but does not state whether the tool is read-only or has any side effects. This is a significant gap for a tool that likely performs network requests.
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 with no wasted words. The action ('Compare 2-5 entities side by side') is front-loaded, and the description efficiently covers purpose, data sources, and efficiency benefit.
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 description is complete for a comparison tool, covering input, output (paired data + URIs), and efficiency. However, no output schema exists, and the return structure is only vaguely described, which could be improved with explicit formatting details.
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, but the description adds meaning by detailing what data is returned per type (e.g., revenue for companies, trial counts for drugs). This enriches the schema's enum and array 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 compares 2-5 entities side by side, with explicit differentiation between 'company' and 'drug' types. It distinguishes itself from sibling tools (e.g., pipedrive tools, memory tools) by its unique comparison functionality.
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 it replaces 8-15 sequential agent calls, indicating efficiency gains. However, it does not specify when not to use it (e.g., for single entity lookup) or provide explicit alternatives.
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?
No annotations provided, so the description carries full burden. It states that the tool searches and returns the most relevant tools with names and descriptions, which is transparent. However, it does not disclose if there are any side effects or 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?
Three sentences, each serving a purpose: what the tool does, what it returns, and when to use it. No 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?
Given the tool's simplicity (2 params, no output schema), the description covers the necessary information: purpose, usage context, and parameter hints. The context signals indicate 100% schema coverage, so the description complements it well.
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%, but the description adds value by explaining the query parameter as a 'natural language description' with examples. It also mentions defaults and max for the limit parameter. However, the description does not elaborate beyond what the schema says.
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 purpose: searching a tool catalog by describing what you need, and returning relevant tools with names and descriptions. It distinguishes itself from sibling tools by being a meta-tool for discovering other tools.
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 call this FIRST when there are 500+ tools available to find the right ones, providing clear when-to-use guidance. Although it does not specify when not to use it, the context of having many tools makes this appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetCInspect
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 must carry full burden. It states it deletes but doesn't disclose if deletion is permanent, reversible, or if confirmation is needed. Lacks behavioral details.
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, no wasted words. Front-loaded with action 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?
Given low complexity (1 required param) but no output schema or annotations, the description is complete for the action but lacks safety and side-effect context expected for a deletion tool.
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 a clear description for 'key'. Description adds no extra meaning beyond the schema, so 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?
Description clearly states the verb (Delete) and resource (stored memory by key), distinguishing it from siblings 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; no mention of prerequisites or conditions. The description is minimal and does not help the agent decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipedrive_get_dealCInspect
Get complete details for a specific deal (by ID). Returns title, value, stage, probability, owner, associated contacts, and timeline.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Deal ID | |
| _apiKey | Yes | Pipedrive API token |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | No | Deal details |
| success | No | Whether the request succeeded |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It does not mention that the tool requires a valid API key, the format of the response, or any potential errors (e.g., deal not found). Simply states 'Get a single deal by ID' without additional context.
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, no wasted words. Front-loaded with action and resource. Could include a brief note about response or prerequisites without losing conciseness.
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?
Tool has two required parameters (API key and deal ID) and no output schema. Description doesn't mention that an API key is needed or what the response contains. For a simple retrieval tool, more context about authentication and return format would be helpful.
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 schema already documents both parameters. Description adds no extra meaning beyond what's in the schema. Baseline score 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 the action (Get) and resource (single deal by ID) from a specific source (Pipedrive). Distinguishes from sibling tools like pipedrive_list_deals and pipedrive_search which handle multiple deals or search functionality.
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. Siblings like pipedrive_list_deals and pipedrive_search exist, but description doesn't mention them or indicate that this tool is for fetching a specific deal by ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipedrive_get_personAInspect
Get full contact details by ID. Returns name, emails, phones, organization, associated deals, and custom fields.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Person ID | |
| _apiKey | Yes | Pipedrive API token |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | No | Contact details |
| success | No | Whether the request succeeded |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose all behavioral traits. It correctly states it is a read operation (get) and returns a single person. It does not mention what happens if the ID is invalid or missing, or any authorization details beyond the API key parameter. This is adequate but 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?
The description is a single, concise sentence that front-loads the core action and resource. 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 simplicity (2 required parameters, no output schema, no nested objects), the description is reasonably complete. It identifies the tool's purpose and key input. However, it does not describe the return value or error conditions, which would be helpful for completeness.
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% (both 'id' and '_apiKey' have descriptions). The description adds no additional meaning beyond what the schema already provides. The baseline of 3 is appropriate since the schema does the heavy lifting.
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 clear verb-resource pair: 'Get a single person (contact) by ID from Pipedrive.' It specifies the resource (person/contact), the action (get), and the source (Pipedrive). This distinguishes it from sibling tools like pipedrive_list_persons and pipedrive_search, though it could be slightly more explicit about being a single-item 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?
No explicit when-to-use or when-not-to-use guidance is given. However, the description implies it is for retrieving a specific person when the ID is known. Given sibling tools like pipedrive_list_persons (for listing) and pipedrive_search (for searching), a savvy agent might infer usage, but there is no direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipedrive_list_dealsCInspect
View all deals in your pipeline. Returns deal IDs, titles, values, stages, and owners. Use pipedrive_get_deal for full details on a specific deal.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (max 500, default 50) | |
| start | No | Pagination start (default 0) | |
| status | No | Filter by status: open, won, lost, deleted, all_not_deleted (default: all_not_deleted) | |
| _apiKey | Yes | Pipedrive API token |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | No | List of deals |
| success | No | Whether the request succeeded |
| additional_data | No | Pagination and metadata |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description carries full burden. It does not disclose that this is a read-only operation, pagination behavior (beyond schema), rate limits, or any side effects.
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. It is front-loaded and free of extraneous information.
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 4 parameters, no output schema, and no annotations. The description fails to explain return format, sorting, or any limitations (e.g., max results beyond schema).
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 each parameter (limit, start, status, _apiKey). The description adds no extra meaning beyond the schema, so 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 clearly states the action ('list') and the resource ('deals from Pipedrive CRM'). It distinguishes from siblings like 'pipedrive_get_deal' (single deal) and 'pipedrive_search' (search across entities).
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 versus alternatives like 'pipedrive_search' or 'pipedrive_get_deal'. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipedrive_list_personsBInspect
View all contacts in your CRM. Returns names, email addresses, phone numbers, and associated organizations and deals.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (max 500, default 50) | |
| start | No | Pagination start (default 0) | |
| _apiKey | Yes | Pipedrive API token |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | No | List of contacts |
| success | No | Whether the request succeeded |
| additional_data | No | Pagination and metadata |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It correctly implies a read-only operation ('List'), which aligns with expected behavior. However, it does not mention any rate limits, pagination behavior beyond what's in the schema, or any side effects. Since there are no annotations to contradict, a mid score is appropriate.
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?
One short sentence, no waste. It is front-loaded with the verb. Could be slightly improved by adding a brief usage note, but it is appropriately concise.
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 that the tool is a simple list operation with a schema covering all parameters and no output schema, the description is adequate. It tells the agent what it does. However, it could mention that results are paginated or that it returns all persons by default, which is partially covered by the schema but not explicitly stated in the description.
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 baseline is 3. The description adds no parameter information beyond the schema (e.g., no mention of optional filters or sorting). It simply restates the resource type, which is already in the name.
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 'List' and resource 'persons (contacts) from Pipedrive', distinguishing it from sibling tools like pipedrive_get_person (get one person) and pipedrive_list_deals (list deals). It is specific and leaves no ambiguity.
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 versus alternatives. For example, it does not explain when to use list_persons vs search (sibling) for finding persons. It also lacks context about typical use cases or prerequisites beyond the API key.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipedrive_searchCInspect
Search deals, contacts, organizations, products, or files by keyword. Returns matching records with IDs and basic info.
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | Search term | |
| limit | No | Max results (default 50) | |
| _apiKey | Yes | Pipedrive API token | |
| item_types | No | Comma-separated item types to search: deal, person, organization, product, file (default: all) |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | No | Search results grouped by item type |
| success | No | Whether the request succeeded |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does not mention that the tool requires an API key, or that it searches all item types by default. The description is minimal and omits important context like pagination or result format.
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 a single sentence, front-loading the core purpose. However, it could include more detail without becoming verbose.
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 complexity (4 params, no output schema, no annotations), the description is insufficient. It lacks guidance on result structure, pagination (limit param), or how item_types affects behavior. The description barely adds value over the tool name.
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. However, the description adds no value beyond the schema—it does not explain how parameters like 'term' or 'item_types' interact. The description is generic and does not enhance understanding of parameter usage.
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 across multiple entity types in Pipedrive, using a specific verb ('search') and listing the resources. It distinguishes from siblings like pipedrive_get_deal or pipedrive_list_persons by its broad search capability.
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 use for cross-entity searches but does not explicitly state when to use this tool versus specific get/list tools. No exclusion criteria or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pipeworx_feedbackAInspect
Send feedback to the Pipeworx team. Use for bug reports, feature requests, missing data, or praise. Describe what you tried in terms of Pipeworx tools/data — do not include the end-user's prompt verbatim. Rate-limited to 5 messages per identifier per day. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | bug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else. | |
| context | No | Optional structured context: which tool, pack, or vertical this relates to. | |
| message | Yes | Your feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max. |
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 transparency. It discloses the rate limit (5 messages per identifier per day), states that it is free, and specifies content guidelines (describe in terms of Pipeworx tools, no verbatim prompts). This is adequate for a feedback tool, though it could mention what happens after submission (e.g., acknowledgment).
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 three sentences: first states the main action, second lists use cases, third adds constraints and guidelines. It is concise, front-loaded, and contains no unnecessary words. Every sentence contributes 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 the tool's simplicity (sending feedback) and the lack of output schema, the description covers essential aspects: purpose, when to use, parameter guidelines, and constraints. It does not mention return values or typical response, but for a feedback tool, this is a minor omission. Overall, it is sufficiently complete for an AI agent to use 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 has 100% description coverage, but the description adds meaningful behavioral guidance for the parameters. For the 'type' parameter, it reinforces the enum options. For 'message', it adds advice on specificity and length ('1-2 sentences typical, 2000 chars max'), which goes beyond the schema description. This extra context improves an AI agent's ability to use the tool correctly.
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 purpose: sending feedback to the Pipeworx team. It lists specific use cases (bug reports, feature requests, data gaps, praise) and distinguishes it from sibling tools, none of which serve a similar 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 says when to use the tool (for the listed feedback types) and provides important guidelines: describe using Pipeworx tools/data, avoid including the end-user's prompt verbatim, and notes the rate limit of 5 messages per day. It does not explicitly state when not to use it, but the tool is self-contained and no sibling serves as an alternative for feedback.
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?
With no annotations provided, the description must carry the burden. It discloses that the tool retrieves stored memories and can list all if key is omitted. However, it does not mention any side effects (none expected for retrieval), permissions, or whether the data persists across sessions (it says 'previous sessions'). The description is straightforward but could benefit from mentioning that it is a read-only operation.
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 with no filler. It is front-loaded with the core action and includes the optional behavior in the same sentence. Every word is necessary.
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 low complexity (1 optional param, no output schema, no nested objects), the description is adequate. It covers the main use cases and clarifies the key omission behavior. No significant gaps remain.
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 a description for the only parameter 'key'. The description adds context by explaining that omitting the key lists all memories. Since schema coverage is high, 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 clearly states the tool's purpose: to retrieve a memory by key or list all memories. It specifies the action ('retrieve', 'list'), the resource ('memory'), and the optional behavior. This distinguishes it from sibling tools like 'remember' (which presumably stores memories) and 'forget' (which deletes).
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: 'to retrieve context you saved earlier in the session or in previous sessions.' It also implies when to omit the key (to list all). However, it does not explicitly mention when not to use it or provide alternatives among siblings.
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?
No annotations are provided, so the description must disclose behavior. It does so by mentioning persistence differences ('Authenticated users get persistent memory; anonymous sessions last 24 hours'). This adds value beyond the input 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, each adding value: what it does, when to use it, and a behavioral note. 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 simple tool (store a key-value pair), the description is complete. It covers purpose, use cases, and behavioral notes (persistence). No output schema exists, but the tool is straightforward.
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%, and the description adds no further parameter details. Baseline of 3 is appropriate since the schema already documents the 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?
The description uses a specific verb ('Store') and resource ('key-value pair in your session memory'), clearly distinguishing it from sibling tools like 'recall' (which retrieves) and 'forget' (which removes).
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 says 'Use this to save intermediate findings, user preferences, or context across tool calls', providing clear use cases. It does not explicitly mention when not to use it, but the purpose is distinct from siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolve_entityAInspect
Resolve an entity to canonical IDs across Pipeworx data sources in a single call. Supports type="company" (ticker/CIK/name → SEC EDGAR identity) and type="drug" (brand or generic name → RxCUI + ingredient + brand). Returns IDs and pipeworx:// resource URIs for stable citation. Replaces 2–3 lookup calls.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Entity type: "company" or "drug". | |
| value | Yes | For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It describes the return values (ticker, CIK, name, URIs) but does not disclose any behavioral traits such as idempotency, rate limits, or side effects. While it implies a read-like operation, it lacks explicit safety guarantees.
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 extremely concise, using two sentences to convey the core purpose, supported types, input formats, and output. Every word contributes meaning, with 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 tool with two parameters and no output schema, the description adequately covers inputs, outputs, and usage context. It could be enhanced by mentioning error handling or required permissions, but the current level is sufficient for correct invocation.
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 covers both parameters with descriptions. The description adds value by providing concrete examples (AAPL, Apple, 0000320193) and clarifying that the 'value' parameter accepts multiple identifier formats, which enhances understanding beyond the schema's generic string 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's purpose: 'Resolve an entity to canonical IDs across Pipeworx data sources in a single call.' It specifies the supported entity type (company) and the inputs (ticker, CIK, name), distinguishing it from siblings by noting it replaces multiple lookup calls.
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 usage context: single call, supports company type, accepts various identifiers. It implies when to use (for company resolution) and mentions efficiency (replaces 2-3 calls), but does not explicitly state when not to use or compare with alternatives beyond the replacement note.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
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Feature your server to boost visibility and reach more users
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Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
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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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If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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