Wisepanel MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: start initiates a deliberation, poll monitors progress, result retrieves final data, publish shares it, list_runs shows history, and cancel stops a run. The descriptions explicitly differentiate them, preventing misselection.
Naming Consistency5/5
All tools follow a consistent 'wisepanel_' prefix with descriptive action suffixes (e.g., start, poll, result), using snake_case uniformly. This predictable pattern makes the set easy to navigate and understand.
Tool Count5/5
With 6 tools, the server is well-scoped for managing Wisepanel deliberations, covering the full lifecycle from start to publish, plus monitoring and cancellation. Each tool earns its place without bloat or gaps.
Completeness5/5
The toolset provides complete coverage for the deliberation domain: start, monitor (poll), retrieve (result), publish, list runs, and cancel. There are no obvious gaps, enabling agents to handle all expected workflows seamlessly.
Average 4/5 across 6 of 6 tools scored. Lowest: 3.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 14 commits in the last 12 weeks
- Last stable release on March 17, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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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 provided, so the description carries the full burden of behavioral disclosure. It states the action ('Cancel') but does not describe behavioral traits such as whether cancellation is reversible, what happens to the run (e.g., deletion, stopping), permission requirements, rate limits, or response format. For a mutation tool with zero annotation coverage, this is a significant gap, though it minimally indicates a destructive operation.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every part contributing essential information, 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.
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 (a mutation operation to cancel runs), lack of annotations, and no output schema, the description is incomplete. It does not cover behavioral aspects like effects of cancellation, error conditions, or return values, which are crucial for safe and effective use. The description alone is insufficient for a mutation tool with no structured support.
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, with the 'run_id' parameter fully documented in the schema. The description does not add any meaning beyond what the schema provides (e.g., no details on run_id format or examples). With high schema coverage, the baseline score is 3, as the description does not compensate but also does not detract.
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 specific action ('Cancel') and target resource ('a running Wisepanel deliberation'), distinguishing it from siblings like 'wisepanel_list_runs' (list), 'wisepanel_poll' (check status), 'wisepanel_publish' (publish), 'wisepanel_result' (retrieve results), and 'wisepanel_start' (initiate). It uses precise verb+resource phrasing without tautology.
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 context ('a running Wisepanel deliberation'), suggesting it should be used on active runs, but does not explicitly state when to use it versus alternatives (e.g., vs. 'wisepanel_poll' for status checks or 'wisepanel_result' for completed runs) or provide exclusions (e.g., not for completed runs). It offers basic implied guidance but lacks explicit alternatives or when-not-to-use details.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'Makes the deliberation publicly viewable and shareable' and has a prerequisite ('Only works for runs that completed successfully in this session'), adding useful context. However, it lacks details on permissions, rate limits, or error handling, leaving some behavioral aspects unclear.
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 front-loaded with the core action and outcome, followed by a critical constraint. Both sentences earn their place by providing essential information without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation with no annotations and no output schema), the description is reasonably complete. It covers the purpose, usage context, and outcome, but lacks details on return values or error cases, which would be helpful for an agent invoking it. This slight gap prevents a perfect score.
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, with the parameter 'run_id' documented as 'The run ID of a completed deliberation'. The description does not add any additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating further.
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 specific action ('Publish') and resource ('a completed deliberation to the Wisepanel Commons'), distinguishing it from siblings like 'wisepanel_list_runs' or 'wisepanel_cancel'. It specifies the target platform and the outcome ('publicly viewable and shareable'), 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.
Usage Guidelines4/5
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: only for 'runs that completed successfully in this session'. However, it does not explicitly mention when not to use it (e.g., for incomplete runs) or name alternatives like 'wisepanel_result' for viewing results without publishing, which keeps it from a perfect score.
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 of behavioral disclosure. It implies this is a read-only operation ('retrieve'), which is helpful, but doesn't specify other traits like authentication needs, rate limits, or error handling. The description adds some context about when data is available, but lacks details on response format or potential side effects.
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 concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage guidelines. Every sentence earns its place by providing essential information without redundancy, 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.
Completeness4/5
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, 100% schema coverage, no output schema), the description is fairly complete. It covers purpose and usage well, but lacks details on behavioral aspects like response format or error cases. Since no output schema exists, the description could benefit from mentioning what the 'full result' includes, but it's adequate for basic use.
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, with the 'run_id' parameter documented as 'The run ID'. The description doesn't add any meaning beyond this, such as explaining what a run ID is or where to find it. Since the schema does the heavy lifting, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieve the full result of a completed Wisepanel deliberation.' This specifies the verb ('retrieve') and resource ('full result of a completed Wisepanel deliberation'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'wisepanel_poll' or 'wisepanel_list_runs', which could provide overlapping functionality.
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 usage guidelines: 'Only needed if you did not poll the run to completion (e.g., a run from a previous session). If you polled it live, you already have the data.' This clearly states when to use this tool (for previously completed runs not polled live) and when not to use it (if already polled), effectively distinguishing it from alternatives like 'wisepanel_poll'.
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?
With no annotations provided, the description carries the full burden. It discloses the tool's read-only nature (implied by 'List') and output structure, but lacks details on behavioral traits like pagination, rate limits, error handling, or session-specific constraints. It adds basic context but misses deeper operational insights.
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 front-loaded with the core action ('List all Wisepanel deliberation runs'), followed by scope and output details in a single, efficient sentence. Every word adds value without redundancy, making it highly concise and well-structured for quick comprehension.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose and output fields, yet lacks context on how runs are tracked, what 'session' entails, or potential limitations. For a list tool with no structured metadata, more completeness would enhance usability.
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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's function and output. A baseline of 4 is applied as it compensates for the lack of parameters by clarifying the tool's scope and return data.
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 specific action ('List all Wisepanel deliberation runs') and resource ('tracked in this session'), distinguishing it from siblings like 'wisepanel_start' (create) or 'wisepanel_cancel' (terminate). It specifies the scope ('in this session') and output fields (run_id, status, topic, panel size), 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.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'tracked in this session' and listing return fields, suggesting it's for retrieving existing runs. However, it doesn't explicitly state when to use this tool versus alternatives like 'wisepanel_poll' (check status) or 'wisepanel_result' (get detailed outcomes), leaving some ambiguity in sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does so effectively. It discloses key behavioral traits: the long-polling mechanism ('Long-polls up to 15 seconds'), immediate return condition ('returning immediately when panelist responses arrive'), and state management ('Returns new events since last poll'). This covers timing, triggering, and incremental data retrieval without contradictions.
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 front-loaded with the core purpose in the first sentence, followed by two concise sentences that add critical behavioral details. Every sentence earns its place by providing essential information without redundancy, making it highly efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (stateful polling), lack of annotations, and no output schema, the description is largely complete. It explains the operation, timing, and data return logic. However, it does not specify the format or structure of returned 'events', which could be important for an agent to process results, leaving a minor gap.
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%, with the single parameter 'run_id' documented in the schema as 'The run ID from wisepanel_start'. The description does not add any additional meaning beyond this, such as format examples or validation rules, so it meets the baseline of 3 where the schema handles parameter documentation adequately.
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 specific action ('Poll a running Wisepanel deliberation for new events') and resource ('Wisepanel deliberation'), distinguishing it from siblings like wisepanel_start (initiates), wisepanel_cancel (terminates), and wisepanel_result (retrieves final results). It precisely defines the tool's function as retrieving incremental updates during an active deliberation.
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 for when to use this tool ('Poll a running Wisepanel deliberation for new events'), implying it should be used during an active deliberation started with wisepanel_start. However, it does not explicitly state when not to use it (e.g., after deliberation ends) or name alternatives like wisepanel_result for final outcomes, which would elevate it to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behaviors: it returns a run_id immediately, requires polling every 10-15 seconds, handles agent_response events with summaries, and indicates completion status triggers a synthesis. It could improve by mentioning error handling or rate limits.
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 appropriately sized and front-loaded, starting with the core purpose and then detailing usage steps. Every sentence adds value, though it could be slightly more streamlined by reducing repetition in polling instructions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (7 parameters, no output schema, no annotations), the description is largely complete, covering purpose, usage flow, and behavioral aspects. It could be enhanced by briefly mentioning the output format or error cases, but it adequately supports agent invocation.
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 7 parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or practical examples, meeting the baseline for high coverage.
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 explicitly states the tool 'Start a Wisepanel deliberation' with specific verbs ('convenes', 'debate') and resources ('panel of AI models'), clearly distinguishing it from sibling tools like wisepanel_poll or wisepanel_publish by focusing on the initiation phase.
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 guidance on when to use this tool (to start a deliberation) and when not to (e.g., 'Do NOT call wisepanel_result after polling'), and names alternatives for subsequent steps (wisepanel_poll, wisepanel_publish), including polling frequency and event handling.
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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