Govcon Intel
Server Details
GovCon Intel MCP — Compound tools that chain SAM.gov, USAspending,
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
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 4/5 across 10 of 10 tools scored. Lowest: 3.2/5.
Most tools have distinct purposes: govcon_* tools cover specific contracting areas, memory tools are separate, and resolve/compare handle entity operations. However, ask_pipeworx introduces some ambiguity as it effectively subsumes other tools by claiming to pick the right one, which could confuse an agent about when to use it versus specific tools.
Tool names follow no consistent pattern: some use verb_noun (govcon_agency_landscape, compare_entities), others are single verbs (forget, recall, remember), and ask_pipeworx uses a different style. This mix of conventions (snake_case, lowercase verbs) makes the set feel haphazard.
With 10 tools, the server is well-scoped for a specialized government contracting assistant. It provides a focused set of utilities (memory, discovery, Q&A) plus domain-specific tools without being bloated or too minimal.
The tool set covers key government contracting workflows: agency landscape, contractor profiles, opportunity scanning, entity resolution, and comparison. Missing features like advanced filtering or alert setup are minor, and the general Q&A tool (ask_pipeworx) provides fallback coverage for edge cases.
Available Tools
11 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 the full burden. It discloses that the tool selects the right tool and fills arguments, which implies autonomous behavior but does not detail limitations, failure modes, or data freshness. The examples hint at capabilities but a few edge-case disclosures would be helpful.
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 plus examples, with no wasted words. It front-loads the core purpose and immediately gives usage guidance.
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 parameter, no output schema, no nested objects), the description is nearly complete. It explains input, behavior, and provides examples. One could argue for mentioning potential delay or error handling, but it's adequate for the complexity level.
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% for the single parameter 'question', so the schema already documents it. The description adds context by explaining the parameter's purpose in natural language and providing examples, but does not add constraints or formatting rules beyond the schema.
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 takes a natural language question and returns an answer from the best data source, which is a specific verb+resource combination. It distinguishes itself from siblings by emphasizing plain English input and automatic tool selection, contrasting with specialized tools like govcon_opportunity_scan.
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 tells when to use this tool: when you have a question and want the best data source without browsing tools or learning schemas. It provides example questions to guide the user, effectively communicating usage context.
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?
With no annotations provided, the description carries the full burden. It discloses that the tool returns paired data and resource URIs, and implies it is a read operation by returning data from sources like SEC EDGAR and FDA. However, it does not explicitly state whether it is read-only, describe error handling, or mention any authentication 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?
The description is two sentences, tightly packed with key information: the action (compare), constraints (2–5), types, data returned, and efficiency benefit. No 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 tool with no output schema, the description adequately explains what is returned (specific financial metrics for companies, counts for drugs) and mentions resource URIs. It could be more complete by noting potential error cases or data freshness, but it covers the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage. The description adds value by clarifying the format for values (tickers/CIKs for company, names for drug) and reiterating the min/max constraints, which helps correct 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 it compares 2–5 entities side by side, specifies two distinct types (company, drug) and what data each returns. It differentiates from siblings like ask_pipeworx or resolve_entity, which are not comparison 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?
The description gives clear context for when to use it (comparing entities) and even quantifies efficiency gains (replaces 8-15 sequential calls). However, it does not explicitly state when not to use it or point to alternatives, though no sibling tool performs similar comparisons.
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 are provided, so the description carries the full burden. It mentions the tool returns 'names and descriptions' but does not disclose any behavioral traits like read-only nature, side effects, or rate limits. For a search tool, read-only is likely, but it's not stated. This is adequate but not fully 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?
The description is concise at two sentences, each adding value: first sentence defines purpose, second gives usage guidance. 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 low complexity (2 params, no output schema), the description is nearly complete. It explains what the tool does, when to use it, and how to formulate queries. It lacks information about return format or whether it's read-only, but these are minor gaps.
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%, and the description adds value by explaining that 'query' should be a natural language description and suggesting examples like 'analyze housing market trends'. It also clarifies default and max for 'limit'. This goes beyond the schema's minimal 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's purpose: searching a tool catalog by describing a need. It specifies the verb 'search', the resource 'Pipeworx tool catalog', and the method 'by describing what you need'. The unique use case of discovering tools among 500+ options distinguishes it effectively from sibling 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?
The description explicitly advises to call this tool FIRST when many tools are available, providing clear when-to-use guidance. It implies it's for initial discovery, not for specific data retrieval, which sets expectations.
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 are provided, so the description carries full burden. It states the action (delete) but does not disclose whether deletion is irreversible, whether confirmation is needed, or any side effects (e.g., cascading deletes). The description lacks behavioral context beyond the basic 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, concise sentence that front-loads the action. Every word is essential; no wasted 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?
Given the tool's simplicity (1 required param, no output schema), the description is adequate but could be improved by mentioning that the deletion is permanent or that the key must exist. However, the description is complete enough for a straightforward delete operation.
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 the parameter. The description adds no additional meaning beyond what the schema provides for the 'key' parameter. 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 uses a clear verb ('Delete') and specifies the resource ('stored memory') and identifier ('by key'). It distinguishes itself from siblings like 'remember' (store) and 'recall' (retrieve) by indicating the opposite operation.
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 when deletion is needed, but does not explicitly state when to use this tool versus alternatives (e.g., 'forget' vs 'remember' vs 'recall'). No guidance on prerequisites or conditions for deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
govcon_agency_landscapeAInspect
Get contracting activity and market insights for a federal agency (e.g., 'Department of Defense', 'NASA'). Returns spending trends, recent awards, SBIR stats, and top contractors by volume.
| Name | Required | Description | Default |
|---|---|---|---|
| agency | Yes | Federal agency name |
Output Schema
| Name | Required | Description |
|---|---|---|
| agency | Yes | Federal agency name queried |
| analysis | Yes | Analysis type identifier |
| sbir_program | Yes | SBIR/STTR program statistics for agency |
| recent_awards | Yes | Recent award contracts from this agency |
| spending_trends | Yes | Historical spending trends for agency |
| spending_overview | Yes | Agency spending breakdown by category |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not mention any behavioral traits like data freshness, scope limitations, or any destructive/write operations. It is neutral and does not contradict annotations, but could add more transparency about what is included.
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, front-loads the purpose, and provides usage examples. It is concise but could be slightly more structured (e.g., separating overview from usage). 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 has only one parameter, no output schema, and no annotations, the description adequately covers the input requirement and high-level output. However, it lacks details on output format, error handling, or scope of data (e.g., time range of trends).
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 description already explains the 'agency' parameter as 'Federal agency name' and gives examples. The description adds no further semantic detail beyond what the schema provides, so a 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 it provides 'Federal agency contracting landscape — spending overview, recent awards, SBIR program stats, and spending trends', which is a specific verb+resource combination. It is easily distinguishable from siblings like 'govcon_contractor_profile' or 'govcon_opportunity_scan'.
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 to 'Provide an agency name' and gives examples ('Department of Defense', 'NASA', 'NIH'). While it does not mention when not to use it, the context of requiring an agency name implies when it is appropriate. No explicit alternatives are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
govcon_contractor_profileAInspect
Vet a government contractor's registration, federal awards, and spending history. Returns certifications, past performance, award amounts, and contract count. Use when assessing vendor credibility or experience.
| Name | Required | Description | Default |
|---|---|---|---|
| _apiKey | No | SAM.gov API key (optional) | |
| company_name | Yes | Company name (e.g., "Lockheed Martin", "Palantir") |
Output Schema
| Name | Required | Description |
|---|---|---|
| company | Yes | Company name queried |
| analysis | Yes | Analysis type identifier |
| federal_awards | Yes | USAspending award history results |
| sam_registration | Yes | SAM.gov entity registration data |
| sbir_sttr_awards | Yes | SBIR/STTR award history results |
| recipient_profile | Yes | USAspending recipient profile data |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses the tool aggregates data from multiple government sources, implying a read-only, non-destructive operation. However, it does not mention data freshness, rate limits, or whether the API key is required for full functionality.
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, well-structured sentence that immediately conveys the tool's value proposition. It is concise and front-loaded with the key 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 has no output schema and moderate complexity (2 params, 1 required), the description adequately explains what the tool does and what input it expects. It could be improved by hinting at the output structure, but the listed data sources provide reasonable expectations.
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 additional parameter details beyond what the schema provides. The description explains the tool's purpose but does not elaborate on parameters, so a 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?
The description clearly states the tool provides a 'complete government contractor dossier' and lists specific data sources (SAM.gov, USAspending, SBIR/STTR grants). It distinguishes itself from sibling tools like govcon_opportunity_scan and govcon_agency_landscape by focusing on company profiles.
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 to 'Provide a company name', making the usage straightforward. It implies this is for looking up a contractor's profile, but does not explicitly contrast with sibling tools or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
govcon_opportunity_scanBInspect
Search open government contracts and grants by keyword or agency. Returns matching opportunities, set-asides (e.g., 8(a), HUBZone, SDVOSB), deadline dates, and active SBIR solicitations.
| Name | Required | Description | Default |
|---|---|---|---|
| _apiKey | No | SAM.gov API key (optional) | |
| keywords | Yes | Search keywords (e.g., "cybersecurity", "AI machine learning", "cloud infrastructure") | |
| set_aside | No | Set-aside type filter (e.g., "SBA", "8A", "HUBZone", "SDVOSB", "WOSB") |
Output Schema
| Name | Required | Description |
|---|---|---|
| analysis | Yes | Analysis type identifier |
| keywords | Yes | Search keywords used |
| set_aside_filter | Yes | Set-aside type filter applied or 'none' |
| open_opportunities | Yes | Open government opportunities matching keywords |
| sbir_solicitations | Yes | Active SBIR/STTR solicitations matching keywords |
| recent_awards_in_space | Yes | Recent federal awards in this market space |
| set_aside_opportunities | Yes | Set-aside specific opportunities (8(a), HUBZone, etc.) |
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 describes the search scope but fails to disclose behavioral traits like rate limits, authentication requirements (API key is optional but not explained), or whether results are real-time or cached. The description is vague about the output 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 a single sentence that is relatively concise, listing the main search categories. It front-loads the purpose. Could be slightly more structured but is efficient.
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 moderate complexity (3 parameters, no enums), the description covers the tool's scope but lacks details on result format, pagination, or error handling. It is minimally complete but could be improved.
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 schema already describes each parameter. The description adds context that keywords match against 'open SAM.gov opportunities, set-aside contracts...' but does not explain the set_aside parameter further or the _apiKey parameter. 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 tool's purpose: searching for government contracting opportunities across multiple sources (SAM.gov, set-aside contracts, recent awards, SBIR solicitations). The verb 'search' and the resource 'government contracting opportunities' are specific, and it distinguishes itself from sibling tools like 'govcon_agency_landscape' and 'govcon_contractor_profile' which focus on agencies and contractors.
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 keyword-based searching but does not explicitly state when to use this tool versus alternatives. It mentions various contract types but lacks guidance on when to use filtering (set_aside) or prerequisites. No mention of when not to use it.
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?
No annotations provided, so the description carries full burden. It discloses rate-limiting (5 messages per identifier per day) and behavioral guidelines (what to include/exclude). It does not mention output, but given no output schema, this is acceptable.
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 (two sentences plus rate limit note), front-loaded with purpose, and every sentence adds value. 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?
For a simple feedback tool with three parameters and no output schema, the description provides sufficient context: purpose, constraints, and parameter guidance. It is 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% with detailed enum explanations. The description adds minor value (e.g., not including verbatim prompts) but does not significantly enhance parameter understanding beyond schema.
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 is for sending feedback to the Pipeworx team, listing specific use cases (bug reports, feature requests, missing data, praise). This distinguishes it clearly from all sibling 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?
The description provides clear guidance on when to use the tool and includes constraints (do not include end-user prompt verbatim, rate-limited). It lacks explicit when-not-to-use statements, but given distinct purpose, it is sufficient.
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 discloses that the tool can retrieve by key or list all memories, and that it works across sessions. No annotations are provided, so the description carries the full burden, and it adequately covers key behavioral aspects (no destructive effects, read-only operation). It does not mention potential side effects or authorization needs, but for a simple retrieval tool this is sufficient.
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 with no wasted words. The first sentence states the core functionality, and the second provides usage context. 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 the tool's simplicity (1 parameter, no required fields, no output schema), the description is complete. It explains both retrieval modes and cross-session behavior. No output schema exists, so the description could mention return format, but the context of 'retrieve' implies returning the stored data; this is acceptable for a minimal 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?
The input schema has 100% coverage with one parameter ('key'), which is described in the schema as 'Memory key to retrieve (omit to list all keys)'. The description adds that omitting the key lists all stored memories, which aligns with the schema and reinforces the dual behavior. Since schema coverage is high, a baseline of 3 is appropriate, and the description adds context about session persistence, raising the score.
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 previously stored memory by key, or list all stored memories when the key is omitted. The verb 'retrieve' and resource 'memory' are specific, and the behavior for both cases is explicitly described, distinguishing it from sibling tools like 'remember' and 'forget'.
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 guidance on when to use this tool: to retrieve context saved earlier. It implicitly distinguishes from 'remember' (save) and 'forget' (delete) by focusing on retrieval. However, it does not explicitly mention when not to use it or alternative tools beyond the context of the session.
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 behavioral traits: persistence differences for authenticated users (persistent) vs anonymous (24-hour expiry). This adds valuable context beyond what annotations would typically provide.
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 distinct purpose: first defines action, second advises when to use, third notes persistence behavior. No filler or repetition.
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 (2 required params, no output schema), the description is complete. It covers purpose, usage, and persistence behavior. A minor gap is not mentioning that values can be overwritten on same key, but overall adequate.
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 fully documents both parameters. The description adds no additional parameter details beyond the schema, but the examples in the schema are sufficient. 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 tool stores a key-value pair in session memory. It specifies the resource ('session memory') and the action ('store a key-value pair'), distinguishing it from siblings like 'recall' (retrieve) and 'forget' (remove).
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 this tool: to save intermediate findings, user preferences, or context across tool calls. It provides usage context but does not explicitly state when not to use it or name alternatives, though siblings imply alternatives for retrieval and deletion.
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?
With no annotations provided, the description carries full burden. It discloses the operation (resolve, read-like) and outputs but does not mention idempotency, authentication needs, rate limits, or potential side effects. The description is adequate but leaves behavioral aspects unspecified.
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, front-loading the key action and benefit. Every sentence adds relevant information without 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?
Given the tool's simplicity (two parameters, no output schema), the description covers purpose, input examples, and output elements. It lacks details on error handling or edge cases, but for the stated scope 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 description coverage is 100%, baseline 3. The description adds value by providing example formats (e.g., 'AAPL', '0000320193') and clarifying the version constraint for type, but does not significantly extend beyond the schema 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 action ('resolve an entity') and the resource ('canonical IDs across Pipeworx data sources'). It specifies outputs (ticker, CIK, name, URIs) and mentions efficiency gain over multiple calls. However, it does not explicitly differentiate from sibling tools like ask_pipeworx.
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 context on when to use the tool: for resolving entities to canonical IDs with examples of input formats (ticker, CIK, name). It implies efficiency ('replaces 2-3 lookup calls') but lacks explicit when-not-to-use guidance or alternatives.
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
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Feature your server to boost visibility and reach more users
For users:
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
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
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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