dnd5e
Server Details
D&D 5e MCP — wraps the D&D 5th Edition API (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-dnd5e
- GitHub Stars
- 0
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.9/5 across 9 of 9 tools scored. Lowest: 2.9/5.
The D&D-specific tools (get_class, get_monster, get_spell, list_spells) have clear, distinct purposes with minimal overlap, but the general-purpose tools (ask_pipeworx, discover_tools, forget, recall, remember) create ambiguity. For example, ask_pipeworx could potentially handle D&D queries, overlapping with the specific get_* tools, and the memory tools (remember/recall/forget) are clearly distinct from each other but their relationship to the D&D tools is unclear.
Naming conventions are highly inconsistent across the tool set. The D&D tools follow a consistent verb_noun pattern (get_class, get_monster, get_spell, list_spells), but the other tools use various styles: ask_pipeworx (verb_propernoun), discover_tools (verb_noun), and simple verbs (forget, recall, remember). This mixed approach makes the tool set feel disjointed and harder to navigate.
With 9 tools total, the count is reasonable for a server that appears to combine D&D reference data with general-purpose utilities. While slightly high for a pure D&D server, the inclusion of memory management and discovery tools justifies the number. The count doesn't feel excessive or insufficient for the apparent scope.
For D&D data retrieval, the coverage is good but incomplete: it provides read operations for classes, monsters, and spells, but lacks update/delete/create operations (which may be intentional for reference data). However, the server's broader purpose is unclear due to the mixed tool types—it's not evident whether this is primarily a D&D server with added utilities or a general server with D&D as one component, making completeness hard to assess fully.
Available Tools
9 toolsask_pipeworxAInspect
Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question or request in natural language |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: Pipeworx 'picks the right tool, fills the arguments, and returns the result,' which explains the tool's automation and result delivery. However, it lacks details on error handling, rate limits, or authentication needs, leaving some gaps in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by explanatory details and examples. Every sentence adds value—none are redundant or wasteful—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 complexity (natural language processing with automation) and no output schema, the description is mostly complete. It explains the tool's function, usage, and parameter semantics well. However, it doesn't detail the output format or potential limitations, which could be helpful for an AI agent to manage expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single parameter. The description adds value by explaining the parameter's semantics: 'Your question or request in natural language' and provides examples like 'What is the US trade deficit with China?' This clarifies the expected format and use case 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 from data source'), and distinguishes from siblings by emphasizing natural language processing rather than specific structured operations like 'get_spell' or 'list_spells'. The examples further clarify the scope.
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 contrasts with sibling tools that likely require specific parameters or schemas, providing clear guidance that this is the alternative for natural language queries versus structured tool invocations.
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 performs a search based on natural language queries and returns relevant tools. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions, which would be helpful for a search 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 appropriately sized and front-loaded, with two sentences that efficiently convey purpose and usage guidelines. Every sentence earns its place by providing essential information without redundancy or unnecessary details.
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 functionality with 2 parameters) and no annotations or output schema, the description is mostly complete. It covers the core purpose and usage context well, but lacks details on output format (beyond 'names and descriptions') and potential behavioral constraints, which would enhance completeness for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear documentation for both parameters (query and limit). The description adds minimal value beyond the schema, mentioning 'describing what you need' which aligns with the query parameter but doesn't provide additional semantic context. The baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('search', 'returns') and resources ('Pipeworx tool catalog', 'tools with names and descriptions'). It distinguishes itself from sibling tools (like get_class, get_monster) by focusing on catalog search rather than direct data retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
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 this tool versus alternatives, including a specific threshold (500+ tools) and a recommended sequence (first).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetCInspect
Delete a stored memory by key.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Delete' implies a destructive mutation, but the description doesn't disclose whether deletion is permanent, reversible, requires specific permissions, or has side effects. For a destructive operation with zero annotation coverage, this is a significant gap.
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 communicates the core functionality without any wasted words. 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?
For a destructive operation with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after deletion (success confirmation, error conditions), whether the operation is idempotent, or how it relates to the memory system implied by sibling tools.
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 the phrase 'by key' which reinforces the parameter's role but doesn't provide additional semantic context beyond what the schema already 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 action ('Delete') and resource ('a stored memory by key'), making the purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'recall' or 'remember', but the verb 'Delete' provides clear differentiation from read 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 no guidance on when to use this tool versus alternatives. With sibling tools like 'recall' (likely for retrieving memories) and 'remember' (likely for storing memories), there's no indication of when deletion is appropriate versus other memory operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_classAInspect
Get class features, hit dice, proficiencies, and advancement tables. Provide class index (e.g., "barbarian", "wizard", "rogue"). Returns feature progression, proficiency gains, and subclass options.
| Name | Required | Description | Default |
|---|---|---|---|
| index | Yes | Class index name in lowercase (e.g. "wizard", "fighter", "cleric"). |
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 clearly describes a read-only operation ('Get details'), but doesn't disclose behavioral traits like error handling, rate limits, or what happens with invalid indices. The description doesn't contradict any annotations.
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 communicates the tool's purpose and parameter usage. Every word earns its place with no wasted text.
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 read operation with one parameter and no output schema, the description is adequate but has gaps. It doesn't explain what 'details' are returned or error conditions. Without annotations, more behavioral context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single 'index' parameter. The description adds minimal value by restating the parameter concept with examples, but doesn't provide additional semantics beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('for a D&D 5e character class'), and distinguishes it from siblings by specifying it's for character classes rather than monsters or spells. It provides specific examples ('barbarian', 'wizard', 'rogue') to illustrate the domain.
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 by stating it retrieves class details by index name, but doesn't explicitly say when to use this versus alternatives like list_spells or get_monster. No guidance on prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_monsterAInspect
Get monster stats including AC, HP, abilities, skills, senses, and actions. Provide monster index (e.g., "aboleth", "dragon-red-adult", "goblin"). Returns ability scores, skill bonuses, and attack/action details.
| Name | Required | Description | Default |
|---|---|---|---|
| index | Yes | Monster index name in kebab-case (e.g. "goblin", "dragon-red-adult"). |
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 describes the action ('Get full details') and the input requirement ('by its index name'), but does not disclose additional traits like error handling (e.g., what happens if the index is invalid), response format, or any rate limits. This is a moderate gap for a tool with no annotation support.
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, input method, and examples without any wasted words. It is front-loaded with the core action and resource, making it easy to scan and understand 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 low complexity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and input, but lacks details on output (e.g., what 'full details' includes), error cases, or behavioral nuances. For a simple lookup tool, this is minimally viable but leaves gaps in understanding the full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'index' fully documented in the schema as 'Monster index name in kebab-case'. The description adds minimal value beyond this by restating 'by its index name' and providing examples, but does not elaborate on semantics like format constraints or validation rules. This 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 verb ('Get full details') and resource ('for a D&D 5e monster'), making the purpose specific and unambiguous. It distinguishes from siblings like 'get_class' and 'get_spell' by specifying the monster domain, and provides concrete examples ('aboleth', 'dragon-red-adult', 'goblin') that reinforce the scope.
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 implicitly indicates when to use this tool by specifying 'by its index name' and providing examples, which helps differentiate it from sibling tools like 'list_spells' (which likely lists multiple items). However, it does not explicitly state when not to use it or name alternatives, such as when to use 'get_class' or 'get_spell' instead, leaving some ambiguity in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_spellAInspect
Get spell details including damage, range, duration, components, and effects. Provide spell index (e.g., "fireball", "magic-missile", "cure-wounds"). Returns damage dice, range, casting time, and effect descriptions.
| Name | Required | Description | Default |
|---|---|---|---|
| index | Yes | Spell index name in kebab-case (e.g. "fireball", "magic-missile"). |
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 describes the tool's function (retrieving spell details) and input format (index name in kebab-case), but lacks information on potential errors (e.g., invalid index), response format, or any rate limits or authentication needs. It adds basic context but misses deeper behavioral traits.
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, parameter usage, and examples without unnecessary words. It is front-loaded with the core function and uses parentheses to include helpful examples, making every part of the sentence earn its place.
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 (one parameter, no nested objects) and high schema coverage, the description is adequate but incomplete. It lacks an output schema, so it does not explain return values or error handling, which are important for a retrieval tool. The description covers the basics but misses details needed for full contextual 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?
The schema description coverage is 100%, with the parameter 'index' fully documented in the input schema. The description adds minimal value by reinforcing the parameter's purpose and providing examples ('fireball', 'magic-missile', 'cure-wounds'), but does not explain semantics beyond what the schema already states. This 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 with a specific verb ('Get') and resource ('full details for a D&D 5e spell'), and distinguishes it from sibling tools like 'list_spells' by specifying retrieval of details for a single spell rather than listing multiple spells. It includes concrete examples ('fireball', 'magic-missile', 'cure-wounds') to illustrate the scope.
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 for when to use this tool (to get details for a specific spell by its index name) and implicitly distinguishes it from 'list_spells' (which lists spells rather than retrieving details). However, it does not explicitly state when not to use it or mention alternatives like 'get_class' or 'get_monster' for other resource types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_spellsBInspect
Search D&D 5e spells by name or level. Returns spell indices, names, and levels for use with get_spell to fetch full details.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 lists spells but doesn't mention any behavioral traits such as pagination, rate limits, authentication needs, or what 'index names' entail. This leaves significant gaps in understanding how the tool operates.
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 front-loaded with the core action and resource, 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'index names' are, how the list is formatted, or any behavioral aspects like response structure or limitations, which are crucial for an agent to use the tool effectively in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all available D&D 5e spells'), specifying what the tool does. However, it doesn't explicitly differentiate from the sibling tool 'get_spell', which likely retrieves a single spell, leaving some ambiguity about sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about usage scenarios, prerequisites, or comparisons to sibling tools like 'get_spell', leaving the agent without explicit direction for tool selection.
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 and does well by explaining the dual behavior (retrieve by key or list all), session persistence ('saved earlier in the session or in previous sessions'), and the conditional logic based on parameter presence. It doesn't mention error handling or performance characteristics, keeping it at 4.
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 explains the core functionality, the second provides usage context. Every word earns its place in helping the agent understand when and how to use this 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 simple retrieval tool with no annotations and no output schema, the description provides complete usage guidance and behavioral context. It could mention return format or error cases but covers the essential context needed for proper tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The description adds meaningful context by explaining the conditional behavior ('omit key to list all keys') and relating the parameter to the tool's purpose ('memory key to retrieve'), which provides semantic value beyond the schema's technical specification.
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 distinguishes from 'remember' (store) and 'forget' (delete) by focusing on retrieval operations.
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 stores data, specifies storage duration ('Authenticated users get persistent memory; anonymous sessions last 24 hours'), and implies it's for session-scoped data. However, it doesn't cover aspects like error handling or storage limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with two sentences that efficiently convey purpose, usage, and behavioral details without redundancy. Every sentence adds value, and there is no wasted text, 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 (2 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and key behavioral traits like persistence rules. However, it lacks details on return values or error handling, which would be beneficial 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, fully documenting both parameters. The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to.
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 ('Store') and resource ('key-value pair in your session memory'), and distinguishes it from sibling tools like 'forget' (delete) and 'recall' (retrieve). It explicitly mentions what can be 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 distinguishes from siblings by function, though not by naming specific alternatives like 'forget' for deletion.
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.
Discussions
No comments yet. Be the first to start the discussion!