usgswater
Server Details
USGS Water MCP — wraps USGS National Water Information System (NWIS) REST services (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-usgswater
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.8/5 across 8 of 8 tools scored. Lowest: 2.9/5.
Most tools have distinct purposes, such as get_current for instantaneous streamflow, get_daily for daily means, and search_sites for finding sites. However, ask_pipeworx overlaps with discover_tools as both help find or execute tools, which could cause minor confusion. The memory tools (remember, recall, forget) are clearly separate from the USGS data tools.
The naming is mixed with no consistent pattern: some use verb_noun (e.g., get_current, search_sites), others use single verbs (e.g., ask_pipeworx, discover_tools, forget, recall, remember). While readable, the lack of a unified convention reduces predictability. The USGS tools follow a similar style, but the overall set lacks consistency.
With 8 tools, the count is reasonable for a server that combines USGS water data access with general-purpose utilities like memory management and tool discovery. It's slightly heavy due to the inclusion of ask_pipeworx and discover_tools, which seem extraneous to the core USGS focus, but overall well-scoped for its apparent dual-purpose domain.
For the USGS water data domain, the tools cover key operations like getting current and daily streamflow and searching for sites, but there are notable gaps such as missing historical data retrieval, water quality parameters, or site metadata. The memory tools provide session support, but the ask_pipeworx and discover_tools add unrelated functionality, creating a disjointed surface that doesn't fully cover either domain comprehensively.
Available Tools
8 toolsask_pipeworxAInspect
Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question or request in natural language |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a query tool that interprets natural language, selects data sources automatically, and returns results. However, it lacks details on limitations (e.g., rate limits, error handling, or specific data source constraints), which prevents a perfect score.
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 front-loaded with the core functionality, followed by supportive details and examples. Every sentence earns its place by clarifying usage, differentiating from alternatives, or providing concrete examples, with no redundant or vague language.
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 (natural language processing with automatic tool selection) and no output schema, the description is mostly complete. It covers purpose, usage, and parameter semantics well, but lacks information on output format or potential errors, which could aid the agent in handling responses.
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 schema description coverage is 100%, so the baseline is 3. The description adds value by emphasizing the parameter's nature ('question or request in natural language') and providing examples that illustrate expected input formats, enhancing understanding beyond the schema's basic type definition.
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: 'Ask a question in plain English and get an answer from the best available data source.' It specifies the verb ('ask'), resource ('answer'), and mechanism ('Pipeworx picks the right tool, fills the arguments'). It distinguishes from siblings by emphasizing natural language input versus tool-specific 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?
The description explicitly states when to use this tool: 'No need to browse tools or learn schemas — just describe what you need.' It provides clear alternatives (implicitly, use other tools for structured queries) and includes three concrete examples to illustrate appropriate use cases, making it highly actionable for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_toolsAInspect
Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of tools to return (default 20, max 50) | |
| query | Yes | Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by explaining the search behavior ('Returns the most relevant tools with names and descriptions') and the 'FIRST' call recommendation. It doesn't detail rate limits, authentication needs, or error handling, but covers core functionality adequately.
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 front-loaded with the main purpose, followed by usage guidance in two sentences. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.
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 moderate complexity (search function with 2 parameters), no annotations, and no output schema, the description is mostly complete. It explains what the tool does and when to use it, but lacks details on output format or error cases, which could be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('query' and 'limit'). The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints, meeting the baseline for high coverage.
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 with specific verbs ('Search the Pipeworx tool catalog') and resource ('tool catalog'), distinguishing it from sibling tools like 'get_current', 'get_daily', and 'search_sites' by focusing on tool discovery rather than data retrieval or site searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidelines: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This gives clear context on when to use it (large catalog, initial search) and implies alternatives are not needed first in such scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetBInspect
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deletes a memory, implying a destructive mutation, but lacks details on permissions, reversibility, error handling, or side effects. This is inadequate for a mutation tool with zero annotation coverage.
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, efficient sentence with zero waste. It is front-loaded with the core action ('Delete') and resource ('stored memory'), making it easy to parse and understand quickly without unnecessary elaboration.
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 destructive mutation tool with no annotations and no output schema, the description is incomplete. It fails to address critical aspects like what happens after deletion (e.g., confirmation, error messages), whether the operation is permanent, or any dependencies, leaving significant gaps for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'key' documented as 'Memory key to delete'. The description adds minimal value beyond this, only reinforcing the parameter's purpose without providing additional context like key format or examples. Baseline 3 is appropriate when 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 clearly states the specific action ('Delete') and resource ('a stored memory by key'), distinguishing it from sibling tools like 'recall' (retrieve) or 'remember' (store). It uses precise language that directly communicates the tool's function without 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an existing memory key), exclusions, or comparisons to siblings like 'recall' (for retrieval) or 'remember' (for storage), leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_currentBInspect
Get current instantaneous streamflow (discharge, cfs) and gage height (ft) for a USGS monitoring site.
| Name | Required | Description | Default |
|---|---|---|---|
| site_id | Yes | USGS site number (e.g., "01646500" for Potomac River at Little Falls, MD) |
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 what data is retrieved but doesn't disclose behavioral traits like rate limits, authentication needs, response format, error conditions, or whether this is a read-only operation. The description doesn't contradict annotations (none exist), but it lacks essential operational context for a tool with no annotation coverage.
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, efficient sentence that front-loads the core functionality ('Get current instantaneous streamflow...'). Every word earns its place by specifying data types, units, and scope without redundancy. It's appropriately sized for a simple tool with one parameter.
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 (1 parameter, no nested objects) and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more behavioral context (e.g., response structure, error handling). The description covers the basic purpose but leaves operational details unspecified, which could hinder an agent's ability to use it correctly without trial and error.
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 the single parameter 'site_id' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to given the schema's completeness.
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 with specific verbs ('Get current instantaneous') and resources ('streamflow (discharge, cfs) and gage height (ft) for a USGS monitoring site'). It distinguishes from sibling tools by specifying 'current instantaneous' data rather than daily aggregates (get_daily) or site searches (search_sites). However, it doesn't explicitly contrast with siblings in the text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'current instantaneous' data, suggesting this tool is for real-time measurements rather than historical or search functions. However, it doesn't provide explicit guidance on when to use this versus alternatives like get_daily for daily averages or search_sites for finding sites. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_dailyAInspect
Get daily mean streamflow values for a USGS site over a date range. Dates must be in YYYY-MM-DD format.
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | End date in YYYY-MM-DD format | |
| start | Yes | Start date in YYYY-MM-DD format | |
| site_id | Yes | USGS site number |
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 discloses the date format requirement (YYYY-MM-DD) which is useful behavioral context, but doesn't mention other important traits like rate limits, authentication needs, error handling, or what happens with invalid dates/sites. The description doesn't contradict any annotations (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that are front-loaded with the core purpose followed by an important constraint. Every word earns its place with no redundant information or unnecessary elaboration.
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 read-only data retrieval tool with no annotations and no output schema, the description provides adequate but minimal context. It covers the purpose and date format requirement, but doesn't explain what the return values look like (e.g., data structure, units) or address potential limitations. Given the tool's relative simplicity, this is minimally viable but has clear 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%, so the schema already fully documents all three parameters. The description adds the date format constraint (YYYY-MM-DD) which provides additional semantic context beyond the schema's parameter descriptions. This meets the baseline expectation when schema coverage is high.
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 specific action ('Get daily mean streamflow values'), resource ('for a USGS site'), and scope ('over a date range'). It distinguishes from sibling tools like 'get_current' (which likely provides current data) and 'search_sites' (which searches for sites rather than retrieving data).
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 retrieving historical daily mean streamflow data, but doesn't explicitly state when to use this tool versus alternatives like 'get_current' (for real-time data) or 'search_sites' (for finding sites). No explicit when-not-to-use guidance or prerequisites are provided.
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 carries the full burden of behavioral disclosure. It adequately describes the core behavior (retrieval vs listing based on parameter presence) and mentions persistence across sessions. However, it doesn't address potential limitations like memory size constraints, retrieval failures, or authentication requirements that might be relevant for a memory system.
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 perfectly concise with two sentences that each earn their place. The first sentence states the dual functionality, and the second provides usage context. There is zero wasted text, and the information is front-loaded with the core purpose immediately clear.
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 retrieval tool with 1 optional parameter and 100% schema coverage, the description provides good context about persistence across sessions and the dual retrieve/list behavior. However, without an output schema, it doesn't describe what format memories are returned in (e.g., structured data, text) or potential error conditions, leaving some gaps in 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?
The schema has 100% description coverage, so the baseline is 3. The description adds valuable semantic context by explaining the dual functionality: retrieving by key versus listing all when key is omitted. This clarifies the optional parameter's significance beyond what the schema's technical description provides, justifying a score above baseline.
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 with specific verbs ('retrieve', 'list') and resources ('previously stored memory', 'all stored memories'). It distinguishes this tool from siblings like 'remember' (which likely stores memories) and 'forget' (which likely deletes them) by focusing on retrieval operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'to retrieve context you saved earlier in the session or in previous sessions.' It also specifies when to omit the key parameter ('omit key to list all keys'), giving clear operational instructions. This distinguishes it from alternatives like 'get_current' or 'get_daily' which likely serve different retrieval purposes.
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 of behavioral disclosure. It effectively describes key traits: the tool performs a write operation ('store'), specifies persistence behavior ('authenticated users get persistent memory; anonymous sessions last 24 hours'), and hints at session-scoped storage. However, it lacks details on error handling, size limits, or concurrency implications.
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 front-loaded with the core purpose in the first sentence, followed by usage context and behavioral details. Every sentence adds value without redundancy, and the structure is efficient with no wasted words, making it easy to parse quickly.
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 moderate complexity (write operation with persistence nuances), no annotations, and no output schema, the description does a good job covering purpose, usage, and key behaviors. However, it lacks information on return values or error cases, which would be helpful for an agent invoking the tool. It compensates well but isn't fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('key' and 'value') thoroughly. The description does not add significant meaning beyond the schema, such as explaining parameter interactions or constraints. The baseline of 3 is appropriate since the schema handles most of the parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('store a key-value pair') and resources ('in your session memory'), distinguishing it from siblings like 'recall' (retrieval) and 'forget' (deletion). It explicitly mentions what gets stored ('intermediate findings, user preferences, or context across tool calls'), making the purpose unambiguous.
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 this tool ('to save intermediate findings, user preferences, or context across tool calls'), but does not explicitly mention when not to use it or name alternatives. It implies usage for persistence needs without detailing scenarios where other tools like 'recall' might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_sitesCInspect
Find active USGS stream-gage sites in a US state that have real-time instantaneous data.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | Two-letter US state abbreviation (e.g., "VA", "CA", "TX") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'active' sites and 'real-time instantaneous data,' which hints at read-only behavior, but doesn't clarify permissions, rate limits, or response format. This leaves significant gaps for a tool that likely queries a database.
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 efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with key information, making it easy for an agent to parse quickly.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., list of sites, error handling) or behavioral aspects like data freshness or limitations, which are crucial for a search tool with real-time data.
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, fully documenting the 'state' parameter. The description adds no additional parameter semantics beyond what the schema provides, such as format details or constraints, so it meets the baseline score for high schema coverage.
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 with specific verbs ('Find active USGS stream-gage sites') and resources ('in a US state that have real-time instantaneous data'). It distinguishes the type of sites (active with real-time data) but doesn't explicitly differentiate from sibling tools like 'get_current' or 'get_daily', which prevents a perfect score.
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 no guidance on when to use this tool versus the sibling tools ('get_current' and 'get_daily'). It implies usage for finding sites with real-time data but lacks explicit when/when-not instructions or alternative recommendations, leaving the agent to infer context.
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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