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wnbhr

being-mcp-server

by wnbhr

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation4/5

    Most tools have distinct purposes, but recall_memory and search_memory both search memory with different parameters, causing potential confusion. Others are clearly separated.

    Naming Consistency4/5

    Majority follow verb_noun pattern (e.g., conclude_topic, merge_nodes, search_memory). Remote_exec slightly breaks consistency with an adjective-noun combination, and get_current_time uses multiple adjectives, but overall pattern is maintained.

    Tool Count5/5

    10 tools are well-scoped for a system that manages memory, relationships, topics, remote execution, and history. Neither too few nor too many.

    Completeness4/5

    Covers core operations for the domain: memory CRUD (search, update, merge, patrol), topic management, history, and remote execution. Minor gaps like explicit node deletion or listing topics could exist, but not severe.

  • Average 3.5/5 across 10 of 10 tools scored. Lowest: 2.9/5.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 1 community issues answered or closed in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are present, so the description must fully disclose behavior. It only says 'merge... into one,' omitting details about whether original nodes are deleted or how conflicts are resolved. This is insufficient 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is concise at one sentence, but it may be too terse. No wasted words, but could include more context without harming conciseness.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a mutation tool with no output schema and three parameters, the description lacks key details: what happens to the original nodes, what the result looks like, and any side effects. This is incomplete.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, with all parameters described. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('merge') and resource ('memory nodes'), specifying that it merges multiple similar nodes into one. However, it does not differentiate from sibling tools like update_memory or update_relation.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    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. It does not mention prerequisites, conditions, or exclusions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so the description carries full burden. It only states 'read/write' without disclosing side effects, error behavior, idempotency, or authorization needs. The list of targets adds minimal behavioral insight.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence with no wasted words. Front-loaded with the key action 'read/write', directly informative and efficient.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (read/write to multiple memory types) and absence of output schema, the description is too sparse. It lacks information about return values, error conditions, or usage patterns.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    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 all parameters. The description adds a readable list of target examples but does not enhance understanding beyond the schema's property descriptions. Baseline 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states 'read/write partner memory' with explicit examples like preferences, knowledge, relationship, etc., making the verb and resource clear. It broadly covers the tool's capabilities but does not differentiate from sibling tools like update_relation which also deals with relationship memory.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool vs alternatives such as recall_memory or search_memory. No exclusions or context about prerequisites or typical scenarios.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    The description only says 'Update relationships' which implies mutation, but no details are given about side effects (e.g., replacing vs. additive), required permissions, or error conditions. With no annotations, the burden falls entirely on the description, and it fails to disclose 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, clear sentence. It is concise and front-loaded with the purpose. However, it could be slightly more informative without becoming verbose.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the absence of an output schema and annotations, the description should provide more context about expected results, error handling, or relationship between parameters (e.g., content required for upsert). It currently lacks completeness for an effective tool description.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 100% description coverage, so the schema already documents all parameters. The description adds no further semantic value beyond listing entity types. Baseline 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool updates relationships with external entities and lists examples (people, devices, AIs, organizations). The verb 'Update' is specific but could be misleading because the action parameter includes 'delete'; however, the sibling tools are distinct, so no confusion.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    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. There is no mention of prerequisites, limitations, or context that would help an agent decide to select this tool over others.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, and the minimal description does not disclose behavioral traits such as whether it's read-only, rate limits, or side effects, leaving agents uninformed about safety.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence with no extraneous words. Front-loaded with verb and resource, achieving efficient communication.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Description is adequate for a simple search tool, but lacks details on return format, pagination, or behavior when no results found, which are important for agent usage.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so parameters are already well-documented. The description adds marginal value by bundling 'by keyword or date', but does not enhance understanding beyond the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly indicates the tool searches past conversation history by keyword or date, distinguishing it from similar memory-search tools like search_memory by specifying 'conversation history'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool versus alternatives like search_memory or recall_memory, nor any prerequisites or exclusion criteria.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    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 only states 'search' which implies read-only, but does not disclose what 'relevant nodes' means, or if there are any side effects. Minimal behavioral context is added beyond the action.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, concise sentence. It is front-loaded and efficient, though slightly sparse for a tool with 4 parameters.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Without an output schema, the description should explain return values or behavior, but it does not. For a search tool with multiple parameters, more context is needed to understand the result structure and effect of options like 'no_nodes'.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so baseline is 3. The description does not add additional meaning to parameters like 'query' or 'limit'; it relies entirely on the schema descriptions.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action 'search' on the resource 'memory graph' and specifies the scope 'in a specific cluster'. This distinguishes it from broader tools like search_memory, making the purpose specific and unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage when searching within a specific cluster, but lacks explicit guidance on when to prefer this tool over alternatives like search_memory. 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.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Given no annotations, the description carries full burden. It discloses archiving (state change) and saving summary, but does not elaborate on side effects like reversibility or permissions.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence of 10 words, efficiently front-loads the action with no wasted words.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description covers the main action but lacks explanation of return values (no output schema) and behavioral details for a mutation tool. Adequate but not comprehensive.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%. The tool description does not add any additional meaning beyond what the input schema already provides for the two parameters.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the verb (archive, save) and resource (current topic, summary, pinned context). It distinguishes from siblings like search_memory or update_memory by focusing on concluding a topic.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    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, nor any prerequisites or when-not-to-use conditions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description must disclose behavioral traits. It states the tool 'extracts scenes' and 'generates memory nodes,' implying it creates or modifies persistent state, but it does not clarify if this is a read-only operation, what side effects occur (e.g., deletion of previous markers), or any rate limits or authorization beyond the env var.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is one concise sentence plus a single prerequisite statement. Every word earns its place; no filler or redundant information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    While the description clarifies the tool's core function and a key prerequisite, it lacks details about the output (no output schema provided) and the exact nature of 'memory nodes' or 'scenes.' For a tool with only two parameters and no complex return value, the description is adequate but could be more complete by mentioning what the tool returns.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema documents both parameters with descriptions (100% coverage), so the description adds minimal value beyond mentioning the LLM_API_KEY requirement. The parameter semantics are adequately clear from the schema alone.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states the tool's action: 'Run patrol — extract scenes from conversation and generate memory nodes.' It uses a specific verb ('run') and resource ('patrol'), and the resulting extraction and generation distinguish it from sibling tools like 'search_memory' or 'conclude_topic'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description mentions the prerequisite 'Requires LLM_API_KEY env var,' providing some guidance on when the tool is usable. However, it does not specify when to use this tool versus alternatives like 'recall_memory' or 'search_history,' nor does it give any '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.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so the description should disclose behavioral traits. It implies a read-only search and mentions that the 'when' field includes evolution history, but does not explicitly confirm no side effects or state changes. Partially adequate.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two concise sentences, front-loaded with the core purpose, and each sentence adds specific detail without redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    With no output schema, the description does not specify the return format (e.g., list of full nodes or IDs). It covers input semantics well but lacks output details. Given the tool's complexity and sibling tools, more context on results would be beneficial.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100% with descriptions, but the description adds meaningful context: space-separated terms are OR-searched by default, mode='and' requires all terms, and the 'when' field includes history. This adds value beyond the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool searches memory nodes by keywords across specific fields (action, feeling, themes, when), and explains default OR vs AND mode. This distinguishes it from siblings like 'recall_memory' (likely exact recall) and 'merge_nodes' (modification).

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly explains the default OR behavior and how to use AND mode. It does not directly state when not to use the tool or compare to alternatives, but the context is clear enough for typical usage.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It discloses the timezone but does not elaborate on other behavioral aspects like idempotency or potential errors. The description is adequate but not rich.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, front-loaded sentence with no wasted words, efficiently conveying the tool's purpose.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple tool with no parameters and no output schema, the description fully conveys the necessary information: the action and the timezone.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With zero parameters, the description adds no parameter information, but the schema coverage is 100%. The baseline for 0 params is 4.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The tool clearly states that it gets the current time in Asia/Tokyo timezone, distinguishing it from sibling tools that perform other tasks.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides clear context by specifying the timezone, but does not explicitly discuss when to use or avoid this tool. However, for a simple time retrieval tool, the context is sufficient.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description fully covers behavioral traits: HTTPS transport, auth token requirement, default-deny allowlist, and that token values are never returned. This is comprehensive for a secure execution tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is one paragraph of 5 sentences, efficiently conveying all necessary information without redundancy. Could be slightly more structured, but it is not verbose.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description does not mention the return value or output format (e.g., stdout, exit code). With no output schema, this is a significant gap. It also does not describe timeout behavior beyond mentioning the parameter. Thus incomplete for an execution tool.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so descriptions per parameter are adequate. The description adds context that host is a host_id from remote_hosts and command must be allowlisted, but does not go beyond schema details for stdin and timeout. Baseline 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool executes a shell command on a remote host over HTTPS, with specific resource and action. It implicitly distinguishes from sibling tools which are memory or topic related.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit conditions: requires a remote_hosts entry in partner_tools, otherwise invalid_request error; and commands must be allowlisted, otherwise forbidden error. This guides the agent on prerequisites and failure modes.

    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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