geo
Server Details
Geo MCP — geographic utilities from free public APIs
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-geo
- GitHub Stars
- 0
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Usage analytics
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Tool Definition Quality
Average 3.6/5 across 10 of 10 tools scored. Lowest: 2.9/5.
Most tools have distinct purposes (e.g., geocode vs. reverse_geocode, get_country vs. get_timezone), but ask_pipeworx and discover_tools overlap significantly as both help users find or access tools/data, which could cause confusion. The memory tools (remember, recall, forget) are clearly distinct from geographic tools.
Naming is inconsistent with mixed patterns: some use verb_noun (e.g., get_country, get_timezone), others use noun only (e.g., geocode, reverse_geocode), and some are vague or compound (e.g., ask_pipeworx, discover_tools). There is no uniform convention across the set.
With 10 tools, the count is reasonable for a server named 'geo' that includes geographic and utility functions. It's slightly high given the core geographic focus, but not excessive, as tools like memory management and discovery add useful capabilities without overwhelming.
For geographic operations, there is good coverage of basics (geocoding, reverse geocoding, country info, timezone, sunrise/sunset), but lacks advanced features like distance calculation, mapping, or routing. The inclusion of memory and discovery tools broadens scope but creates a disjointed surface with minor gaps in the geographic domain.
Available Tools
10 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: the tool interprets natural language questions, selects appropriate data sources, and returns results. However, it lacks details on limitations (e.g., response time, error handling) or authentication needs, though this is partially mitigated by the simple single-parameter design.
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 supporting details and examples. Every sentence adds value: the first explains the tool's purpose, the second describes its automation benefits, and the third provides concrete examples. No wasted words or redundant 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 complexity (natural language processing and tool selection) and lack of output schema, the description is mostly complete. It explains what the tool does and how to use it, but doesn't detail return formats or potential errors. For a tool with no annotations and simple parameters, this is adequate though not exhaustive.
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, so the baseline is 3. The description adds value by explaining the parameter's purpose in context: 'Your question or request in natural language' and providing examples like 'What is the US trade deficit with China?' This clarifies the expected format and scope beyond the schema's basic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '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'), distinguishing it from sibling tools like 'discover_tools' or 'geocode' which have different functions.
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: 'No need to browse tools or learn schemas — just describe what you need.' It contrasts with alternatives by implying this tool handles tool selection internally, unlike other tools that require specific parameters or knowledge. Examples further clarify appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_toolsAInspect
Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of tools to return (default 20, max 50) | |
| query | Yes | Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it's a search operation (implied read-only), returns ranked results ('most relevant'), and has a specific use case (initial discovery). However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions.
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 and well-structured in two sentences. The first sentence explains the core functionality, and the second provides crucial usage guidance. Every word earns its place with no redundancy 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?
Given the tool's moderate complexity (search operation with 2 parameters) and 100% schema coverage, the description provides good contextual completeness. It explains the purpose, when to use it, and the expected output format. The main gap is the lack of output schema, but the description partially compensates by mentioning what gets returned ('tools with names and descriptions').
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 thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain query formatting or limit implications). 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 tool's purpose with specific verbs ('search', 'returns') and resources ('Pipeworx tool catalog', 'most relevant tools with names and descriptions'). It distinguishes itself from sibling tools by focusing on tool discovery rather than geographic or time-related functions like geocode or get_timezone.
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 about when to use it (large tool catalog, initial discovery phase) and implicitly suggests alternatives (directly using specific tools once identified).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetCInspect
Delete a stored memory by key.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Delete' implies a destructive mutation, the description doesn't specify whether deletion is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting other tools). It also doesn't describe the response format or error conditions, leaving significant behavioral gaps for a mutation tool.
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, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and efficient. Every word earns its place, achieving optimal conciseness for this simple tool.
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 lacks critical context such as what constitutes a valid 'key', whether deletion is idempotent, what happens on success/failure, or how this interacts with sibling tools like 'remember' and 'recall'. The agent would need to guess or trial-error these aspects.
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, with the 'key' parameter fully documented in the schema itself ('Memory key to delete'). The description adds no additional semantic context beyond what the schema provides (e.g., key format, examples, or constraints), so it meets the baseline of 3 for high schema coverage without adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the resource ('a stored memory by key'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'recall' (which presumably retrieves memories) or 'remember' (which presumably stores memories), missing an opportunity for sibling differentiation that would warrant a score of 5.
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. There's no mention of prerequisites (e.g., needing an existing memory to delete), when-not-to-use scenarios, or explicit references to sibling tools like 'recall' or 'remember' for context. This leaves the agent without usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
geocodeAInspect
Convert an address or place name to coordinates. Returns latitude, longitude, and formatted address. Use when you need map positions or spatial analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Address or place name to geocode |
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 conversion function but does not disclose behavioral traits such as rate limits, accuracy considerations, error handling, or authentication needs. For a geocoding tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.
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 (geocoding with one parameter) and no output schema, the description adequately covers the basic purpose. However, it lacks details on return values, error cases, or behavioral aspects, which are important for a tool with no annotations. It 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?
The schema description coverage is 100%, with the single parameter 'query' documented as 'Address or place name to geocode'. The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the 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 specific action ('convert') and resource ('address or place name') to produce the output ('latitude/longitude coordinates'). It distinguishes from sibling tools like 'reverse_geocode' (which does the opposite conversion) and other location-related tools like 'get_country' or 'get_timezone' by focusing on forward geocoding.
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 converting addresses to coordinates but does not explicitly state when to use this tool versus alternatives like 'reverse_geocode' (for coordinates to addresses) or other siblings. It provides basic context but lacks explicit guidance on exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_countryCInspect
Get country information by name or ISO code (e.g., 'US', 'FR'). Returns capital, population, currency, languages, and neighboring countries. Use for regional context or facts.
| Name | Required | Description | Default |
|---|---|---|---|
| code_or_name | Yes | Country name or ISO 3166-1 alpha-2/alpha-3 code |
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 'gets' information, implying a read-only operation, but doesn't disclose behavioral traits such as error handling (e.g., for invalid inputs), rate limits, authentication needs, or what 'detailed information' includes (e.g., format, fields). This leaves significant gaps for an agent to understand how to invoke it correctly.
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 purpose without unnecessary words. Every part earns its place by specifying the action, resource, and lookup method, 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 complexity of a tool with one parameter but no annotations or output schema, the description is incomplete. It doesn't explain what 'detailed information' entails (e.g., response format, fields), behavioral aspects, or usage context relative to siblings. This could hinder an agent from selecting and invoking the tool effectively.
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, with the parameter 'code_or_name' fully documented in the schema. The description adds minimal value beyond the schema by reiterating 'by name or ISO code', but doesn't provide additional semantics like examples or edge cases. With high schema coverage, the 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's purpose with a specific verb ('Get') and resource ('detailed information about a country'), and it specifies the lookup mechanism ('by name or ISO code'). However, it doesn't explicitly differentiate from siblings like 'geocode' or 'reverse_geocode', which might also provide country information in different contexts.
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 doesn't mention siblings like 'geocode' (which might provide location data) or 'get_timezone' (which might include country info), nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sunrise_sunsetBInspect
Get sunrise/sunset times for a location by coordinates or city name. Returns exact times, daylight duration, and twilight times. Use for activity planning or astronomical data.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Date in YYYY-MM-DD format (default: today) | |
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude |
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 what the tool does but lacks details on traits like rate limits, error handling, authentication needs, or response format. For a tool with no annotations, this is a significant gap in transparency.
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: 'Get sunrise and sunset times for a location.' It is front-loaded with the core purpose and has no wasted words, making it highly concise and 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 tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, and output, which are needed for full completeness. It meets the minimum viable standard with 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?
The input schema has 100% description coverage, clearly documenting all parameters (latitude, longitude, date). The description implies location-based parameters but adds no extra meaning beyond the schema. According to the rules, with high schema coverage, the baseline is 3, which is appropriate here.
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: 'Get sunrise and sunset times for a location.' It specifies the verb ('Get') and resource ('sunrise and sunset times'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'get_timezone' or 'geocode,' which might also involve location data, so it's not a perfect 5.
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 doesn't mention sibling tools like 'get_timezone' or 'geocode,' nor does it specify contexts or exclusions for usage. This leaves the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_timezoneCInspect
Get timezone and current local time for coordinates or city name. Returns timezone name, UTC offset, and current time. Use for scheduling across time zones.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude |
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 what the tool does but lacks critical behavioral details: it doesn't specify error handling for invalid coordinates, rate limits, authentication requirements, or the format of the returned timezone and local time. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.
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 directly states the tool's function without unnecessary words. It is front-loaded with the core purpose ('Get the current timezone and local time for a location'), making it easy to understand at a glance. Every part of the sentence earns its place by specifying the resource and context.
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 of a geospatial query tool with no annotations and no output schema, the description is incomplete. It doesn't address how results are returned, potential errors, or dependencies on external services. For a tool that likely interacts with timezone databases or APIs, more context on behavior and output expectations is needed to be fully helpful to an AI 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?
The input schema has 100% description coverage, with clear documentation for both 'latitude' and 'longitude' parameters. The description adds no additional semantic meaning beyond what the schema provides—it doesn't explain coordinate formats, valid ranges, or how the location is used to determine timezone. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.
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 a specific verb ('Get') and resource ('current timezone and local time for a location'). It distinguishes itself from siblings like 'geocode' or 'get_sunrise_sunset' by focusing on timezone data rather than geographic coding or astronomical events. However, it doesn't explicitly differentiate from 'get_country', which might also provide location-based information.
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 doesn't mention when to choose this over 'get_country' for location-based queries or 'reverse_geocode' for coordinate-based lookups. There are no explicit instructions on prerequisites, such as needing valid coordinates, or exclusions for 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.
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 full burden. It discloses key behavioral traits: it can retrieve memories from current or previous sessions, and the conditional behavior based on parameter presence. However, it doesn't mention error handling, data formats, or persistence details that would be helpful for a memory tool.
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 well-structured sentences with zero waste. The first sentence states the core functionality with parameter guidance, the second provides usage context. Every word earns its place in this efficient description.
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 good schema coverage but no annotations or output schema, the description provides adequate context about behavior and usage. It could be more complete by mentioning return formats or error cases, but it covers the essential operational semantics given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, so the baseline is 3. The description adds meaningful context by explaining the conditional behavior: omitting the key triggers listing all memories, while providing it retrieves a specific memory. This clarifies the parameter's semantic role beyond what the schema states.
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 from siblings like 'remember' (store) and 'forget' (delete) 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') and when to omit parameters ('omit key to list all keys'). It implicitly distinguishes from 'remember' for storage and 'forget' for deletion, though it doesn't name alternatives directly.
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 behavioral traits: the tool performs a write operation ('store'), specifies persistence characteristics ('authenticated users get persistent memory; anonymous sessions last 24 hours'), and implies it's for session-scoped data. However, it doesn't mention error conditions, rate limits, or specific authentication requirements beyond the persistence distinction.
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 appropriately sized and front-loaded, with two concise sentences that directly address purpose and behavioral context. Every sentence earns its place by providing essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (a write operation with persistence nuances), no annotations, and no output schema, the description is reasonably complete. It covers purpose, usage context, and key behavioral traits like persistence rules. However, it lacks details on return values, error handling, or specific limitations, which would be helpful for full 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 input schema has 100% description coverage, providing clear documentation for both parameters. The description adds minimal value beyond the schema, as it doesn't elaborate on parameter usage, constraints, or examples. The baseline score of 3 is appropriate since the schema already 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 tool's purpose with specific verbs ('store a key-value pair') and resource ('in your session memory'), and distinguishes it from sibling tools like 'recall' (which presumably retrieves) and 'forget' (which presumably deletes). It also specifies the type of data that can be stored ('intermediate findings, user preferences, or context across tool calls').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool ('to save intermediate findings, user preferences, or context across tool calls'), but does not explicitly state when not to use it or name alternatives. It implies usage for persistence across calls but lacks explicit exclusions or comparisons to other storage mechanisms.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reverse_geocodeCInspect
Convert coordinates to a physical address. Returns street address, city, country, and postal code. Use to identify locations from lat/lng pairs.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude |
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 of behavioral disclosure. It states the conversion action but doesn't reveal any behavioral traits such as accuracy, rate limits, data sources, error handling, or output format. For a tool with zero annotation coverage, this is a significant gap in transparency.
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 directly states the tool's function without any unnecessary words. It is front-loaded and wastes no space, 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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like performance, limitations, or what the returned address includes (e.g., full address, components). For a conversion tool with no structured context, more detail is needed to guide effective use.
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 description mentions 'latitude/longitude coordinates' but doesn't add meaning beyond what the input schema provides. With 100% schema description coverage, the schema already documents both parameters adequately. The description doesn't specify coordinate formats, ranges, or units, so it meets the baseline 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: converting coordinates to an address. It uses specific verbs ('convert') and resources ('latitude/longitude coordinates', 'address'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'geocode' (which likely does the opposite conversion).
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 doesn't mention sibling tools like 'geocode' (reverse operation), 'get_country', 'get_sunrise_sunset', or 'get_timezone', nor does it specify use cases or prerequisites. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
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
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
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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