Trade Intel
Server Details
Trade Intel MCP — Compound tools that chain Comtrade, Census, Treasury,
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.9/5 across 8 of 8 tools scored. Lowest: 3.1/5.
Tools are mostly distinct, but 'ask_pipeworx' acts as a catch-all that overlaps with all other tools, potentially causing confusion about which tool to use. The three trade tools are distinct by function. Memory tools are clearly separate.
Trade tools use a consistent 'trade_' prefix. Memory tools use verb-only names ('remember', 'recall', 'forget'). The 'ask_pipeworx' and 'discover_tools' break the pattern but are descriptive.
With 8 tools, the count is reasonable for a trade intelligence server. The memory tools add a general utility layer, but they don't feel out of place.
The three trade tools cover bilateral analysis, country profiles, and US macro dashboard, which are key areas. However, missing features like commodity-specific queries or tariff data leave some gaps for comprehensive trade analysis.
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?
The description discloses that Pipeworx picks the right tool and fills arguments, implying delegation, which is key behavioral context beyond annotations (none provided). It doesn't detail failure modes or data sources.
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-loaded with purpose and examples, 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?
For a single-parameter tool with no output schema, the description is complete enough, providing examples and explaining the delegation mechanism. However, it could mention limitations or data coverage.
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 single 'question' parameter. The description adds value by explaining it accepts natural language, but the schema already describes it as 'Your question or request in natural language'.
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 answers natural language questions by selecting the best data source, which distinguishes it from siblings like trade_bilateral_analysis or trade_macro_dashboard that are domain-specific.
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 to use this tool for plain English questions and mentions it handles tool selection automatically, but does not explicitly state when not to use it or name 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 are provided, so the description carries the full burden. It states the tool 'Returns the most relevant tools with names and descriptions,' which is useful but lacks details on ranking, exact return format, or whether it's read-only. It does not contradict anything, and a score of 3 is reasonable given the minimal behavioral disclosure beyond the basic 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 extremely concise: two sentences that front-load the purpose and critical usage advice. Every sentence is essential and there is no redundant or 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?
Given the tool's simplicity (2 parameters, no output schema, no nested objects) and the presence of sibling tools, the description covers the key aspects: what it does, when to use it, and the return type (tools with names and descriptions). It could be slightly more explicit about the return format or sorting, but it is largely complete for a search tool with clear 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 description coverage is 100%, so the description need not add much. The description does not elaborate on the parameters beyond what the schema already provides (e.g., query and limit). However, it does not introduce confusion and the schema is clear, so 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 verb ('Search') and resource ('Pipeworx tool catalog'), specifies the purpose ('find the right tools for your task'), and distinguishes this from siblings by its unique role as a discovery/search tool, which is further emphasized by the usage guidance to call it first.
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 the agent to 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear when-to-use guidance and implies when not to use it (when you already know the tool). No alternative tools are named, but the context of 500+ tools and the first-call instruction effectively differentiate it.
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 must carry full behavioral burden. It correctly indicates the destructive nature ('delete'), but does not disclose whether deletion is permanent, irreversible, or affects other operations. A score of 3 is appropriate as it conveys the core behavior but lacks depth.
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 direct and front-loaded. It contains no filler and 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 tool is simple (single parameter, no output schema), the description adequately conveys the purpose. However, it does not specify what happens on success or failure (e.g., returns confirmation, error if key missing), which would be beneficial.
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 single parameter 'key'. The description adds no extra meaning beyond the schema's description. 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 'Delete a stored memory by key' clearly states the verb ('delete'), the resource ('stored memory'), and the mechanism ('by key'). It effectively differentiates from siblings like 'recall' (retrieve) and 'remember' (store).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (when you need to delete a memory), but provides no guidance on when not to use it or alternatives. Given the sibling context, it does not explicitly contrast with similar tools, though the name and purpose are distinct enough.
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?
No annotations provided, so description carries burden. It states the tool retrieves or lists memories, which is clear. However, it doesn't disclose if retrieval modifies anything, requires authentication, or has rate limits. Adequate but minimal beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action, no wasted words. 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), the description fully explains the tool's behavior: retrieve specific or list all. Could mention return format, but not essential for a simple memory 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 one optional parameter described. The description adds 'list all stored memories (omit key)' which adds context beyond the schema's 'omit to list all keys'. This adds moderate value, 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?
Clearly states the verb 'retrieve' and resource 'memory by key' or 'list all stored memories', distinguishing it from siblings like 'remember' (store) and 'forget' (delete).
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 when to use: 'to retrieve context you saved earlier', and implies when not to (use 'remember' to save). Lacks explicit exclusion or alternative names beyond the tool name itself.
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 carries the full burden. It discloses that storage is session-based, with authenticated users getting persistent memory and anonymous sessions lasting 24 hours. This is good behavioral context, but it does not mention any side effects (e.g., overwriting existing keys), limits on key/value sizes, or whether the tool can fail silently.
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, front-loaded with the core action. It efficiently covers purpose, usage, and persistence. Could be slightly more concise by removing 'in your session memory' since that is implicit, but overall well-structured.
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 (two required string parameters, no output schema), the description is mostly complete. However, it lacks information about whether storing an existing key overwrites the value, what happens on failure (e.g., memory full), and the fact that the memory is per-session. These gaps are minor but notable for a complete picture.
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 provides good descriptions for both parameters (key and value), and coverage is 100%. The description adds context about what kinds of values to store (findings, addresses, preferences, notes) and provides example key conventions (e.g., 'subject_property'). This enhances the schema's meaning.
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 ('store a key-value pair'), the resource ('session memory'), and distinguishes the tool by naming its purpose: saving intermediate findings, user preferences, or context across tool calls. This differentiates it from siblings like 'forget' and 'recall'.
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 ('save intermediate findings, user preferences, or context across tool calls') and provides context about persistence differences between authenticated and anonymous sessions. It does not explicitly mention when not to use it or name alternative tools, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trade_bilateral_analysisAInspect
Compare trade flows between two countries. Returns bilateral imports, exports, top commodities, and exchange rates. Use country codes (e.g., 842 for US, 156 for China, 276 for Germany, 392 for Japan, 826 for UK).
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Trade year (default: last year) | |
| _fredKey | No | FRED API key (optional, for dollar index) | |
| partner_code | Yes | Partner country code (e.g., "156" for China) | |
| reporter_code | Yes | Reporting country code (e.g., "842" for US) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral transparency. It discloses that the tool combines multiple data sources and notes that FRED key is optional for dollar index. However, it does not mention potential side effects (e.g., rate limits, cost, or that it is read-only). The description adds value beyond structured fields but lacks completeness.
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, front-loading the main purpose and then adding supporting details. It is efficient, but the first sentence could be slightly more concise. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (combines multiple data sources) and lack of output schema, the description covers the main inputs and data sources but does not explain the output structure, which would help the agent anticipate the return value. It is adequate but incomplete for full understanding.
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. The description adds context by listing country code examples and hinting at the purpose of year and _fredKey. However, it does not elaborate on the meaning of the parameters beyond what the schema already provides, so no higher 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 performs 'complete bilateral trade analysis between two countries in one call,' combining multiple data sources (trade flows, exchange rates, dollar index). It distinguishes itself from siblings like trade_country_profile and trade_macro_dashboard by specifying the bilateral nature and comprehensive data aggregation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for comprehensive bilateral analysis) and provides example country codes, aiding selection. However, it does not explicitly state when not to use it or mention alternatives among siblings, which would improve the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trade_country_profileAInspect
Get a country's trade snapshot: top 10 import/export partners and top 10 commodities. Use country codes (e.g., 842 for US, 156 for China, 276 for Germany, 392 for Japan, 826 for UK).
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Trade year (default: last year) | |
| country_code | Yes | Country code (e.g., "842" for US) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'all in one call' indicating batch behavior, but lacks details on data freshness, rate limits, or potential errors. With no annotations, the description carries full burden and is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and key details. Every sentence adds value with no waste.
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 two-parameter input and no output schema, the description is nearly complete. It covers what the tool returns and key usage notes, though return format details could be 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 description coverage is 100% so baseline is 3. The description adds country code examples but no additional semantic context beyond the schema for the year 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 tool provides a comprehensive trade profile including top import/export partners and commodities. The verb 'trade profile' combined with the resource 'country' is specific and distinguishes it from sibling tools like trade_bilateral_analysis and trade_macro_dashboard.
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 mentions country code examples and the default year behavior. However, it does not explain when to use this tool versus the bilateral or macro dashboard alternatives, leaving room for improvement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trade_macro_dashboardBInspect
Check US trade indicators: customs revenue, exchange rates, trade balance, monthly trends, price indices, and goods/services breakdown.
| Name | Required | Description | Default |
|---|---|---|---|
| _fredKey | No | FRED API key (optional, for macro series) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral traits. It states the tool provides a dashboard of indicators and optionally includes FRED data with an API key, but does not disclose whether data is cached, how often it updates, whether API calls are rate-limited, or if the dashboard requires authentication. The optional API key is mentioned but not explained in terms of behavior change.
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, listing indicators in a single sentence and then adding the optional API key detail in another. It front-loads the main purpose and keeps additional information separate. 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 complexity (dashboard with multiple indicators) and no output schema, the description is somewhat complete but lacks details on what the dashboard returns (e.g., format, time range, default behavior without API key). The single optional parameter and no required fields reduce the need for extensive explanation, but more clarity on output would help.
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 one optional parameter (_fredKey) whose description is basic. The tool description adds context about what the parameter enables ('FRED dollar index and goods/services balance'), which is valuable beyond the schema's brief description. Since there is only one optional parameter, the description adequately supplements it.
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 US trade macro indicators and lists specific categories (customs revenue, exchange rates, trade balance, etc.). It differentiates from sibling tools like trade_bilateral_analysis and trade_country_profile by focusing on macro-level dashboard data rather than bilateral or country-specific analysis.
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 mentions optionally including FRED dollar index with an API key but provides no guidance on when to use this tool vs alternatives, nor any context on prerequisites or typical use cases. The agent is left guessing when this tool is appropriate.
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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