@kjadeja/open-featurebase-mcp

Server Quality Checklist

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Latest release: v1.0.2
Disambiguation5/5
Each tool has a clearly distinct purpose: batch fetch by slugs, list all, get single, search, find stalled promises, and user lookup. No overlap in functionality.
Naming Consistency4/5
All tools follow a verb_featurebase_noun pattern, but verbs like 'get' are used for multiple actions (batch, single, stalled promises) and 'find' vs 'search' introduces minor inconsistency.
Tool Count5/5
Six tools is well-scoped for a Featurebase integration, covering core read operations and a specialized query without being overwhelming or insufficient.
Completeness3/5
The tool set covers reading and searching well, but lacks any write operations (create, update, delete) for posts or comments, which are typical for a feedback board.
Average 3.4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 25 commits in the last 12 weeks
- Last stable release on July 20, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
Without annotations, the description must disclose behavioral traits. It only states the high-level purpose. It does not mention how teamUserIds override works, sorting behavior, or any side effects. The schema descriptions compensate, but the tool description itself is insufficient for behavioral transparency.
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 that is easy to parse and front-loaded. It avoids unnecessary words. However, it could be slightly more structured (e.g., mentioning key parameters like default N days) without losing 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?
Given the tool has 5 parameters, no output schema, and moderate complexity (team override, sorting, status filter), the one-sentence description is too minimal. It does not explain output format, behavior of the 'N' parameter, or nuance like empty teamUserIds. The description is incomplete for an agent to fully understand the tool's capabilities.
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 detailed parameter descriptions. The tool description adds no parameter info beyond what the schema provides. Per rubric, baseline 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds posts where admin replied, customer spoke last, and admin is silent for N+ days. It identifies the specific resource (stalled promises) and verb (find). However, it does not explicitly differentiate from sibling tools like list_featurebase_posts or search_featurebase_posts, which could also retrieve posts with conditions.
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 vs alternatives. The description lacks information about prerequisites (e.g., need for FEATUREBASE_TEAM_USER_IDS env var) or scenarios where this tool is inappropriate. Sibling tool names are listed but not contrasted.
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 description lacks details on behavioral traits such as rate limits, authentication requirements, or potential side effects. It assumes a 'configured' board without explaining setup.
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 own description is concise, but extensive parameter details follow. The structure is front-loaded with the core purpose and then detailed parameter info, which is appropriate.
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 parameter documentation is thorough, the description omits output format, pagination details beyond limit, and error scenarios. Given the lack of output schema, more completeness on return values is needed.
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 schema already covers parameters fully (100% coverage). The description adds significant value by explaining complex behaviors of teamUserIds and hasAdminReply, especially the override logic and error handling.
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 it lists posts from the configured Featurebase board. However, it does not differentiate from sibling tools like get_featurebase_posts or search_featurebase_posts, which likely have similar listing capabilities.
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. The description does not mention prerequisites, when not to use, or any context for selection among siblings.
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?
With no annotations, the description carries the full burden. It only states the basic function, omitting behavioral details like case-insensitivity, scanning scope, or what sampleSize does. The schema provides details, but the description itself is insufficient.
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?
Single sentence, no fluff. It is appropriately sized for the tool's simplicity, though could slightly expand on behavior.
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?
Lacks return value information (no output schema). Given the tool's simplicity and sibling context, it is incomplete for an agent to fully understand the outcome.
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 3. The description does not add meaning beyond the schema; both parameters are fully described in the schema, so no extra value from the description.
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 uses a specific verb ('look up') and resource ('user IDs') with a clear method ('partial name match'). It distinguishes itself from sibling tools, which all relate to posts.
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 for user ID lookup without explicit guidance on when to use versus alternatives. Since all siblings are post-related, context is clear, but no exclusions or when-not-to-use are stated.
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 mentions the basic functionality and optional comment inclusion, omitting key behaviors like error handling (e.g., if slug is not found), authorization requirements, or whether it is a read-only operation. The parameter documentation provides some detail but the main description lacks transparency.
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 sentence of 16 words, efficiently conveying the core purpose. It is front-loaded and lacks fluff, though it could benefit from an extra sentence about usage context 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?
The description is too minimal given the tool's complexity (3 parameters, no output schema). It does not outline the return structure of the post object or the comments data, leaving the agent to infer from the parameter descriptions. Crucial information like required authentication or possible error responses is missing.
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 detailed descriptions for all three parameters. The main description adds only the high-level idea of 'optionally with full comment thread,' which is already implied by the 'include_comments' parameter. Baseline 3 is appropriate as the description adds minimal 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 states 'Get a single post by slug, optionally with full comment thread,' using a specific verb and resource. It clearly distinguishes from sibling tools like 'get_featurebase_posts' (plural) which would fetch multiple posts.
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 for retrieving a specific post given a slug, but it does not explicitly state when to use this tool over alternatives like 'list_featurebase_posts' or 'search_featurebase_posts'. No exclusions or when-not-to-use guidance is provided.
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 must carry the full burden of behavioral disclosure. It states the search scope (title + body), which is helpful, but does not explicitly indicate that the operation is read-only or describe any other behavioral traits. The weighting and tokenization details are in the schema parameter descriptions, but the tool description itself lacks transparency.
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, focused sentence with no filler or extraneous information. Every word contributes to the tool's purpose, making it highly concise and easy to parse.
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?
For a simple search tool with a complete schema, the description covers the core purpose but omits contextual details like result format, sorting, or when to prefer this over other retrieval tools. It is minimally adequate but not fully 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%, so the baseline is 3. The tool description adds minimal context ('by keyword over title + body') beyond what the schema already provides (weighting, tokenization). Thus, it meets the baseline but does not significantly enhance understanding.
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') and the resource ('posts'), and specifies the scope ('by keyword over title + body'). This effectively distinguishes it from sibling tools like list_featurebase_posts (which would list all) and get_featurebase_post (which retrieves by ID).
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?
The description provides no guidance on when to use this tool versus alternatives (e.g., when to search vs list or get). There is no mention of prerequisites, context, or when not to use it, leaving the agent with insufficient decision-making information.
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?
No annotations provided, so description carries full burden. It discloses that posts are returned in order requested and that missing slugs are returned in a 'notFound' field rather than throwing. No mention of auth, rate limits, or destructive behavior. Given read-like name, transparency is good but not exhaustive.
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 main description is a single sentence with no waste. Parameter descriptions are thorough yet concise. Every sentence adds value, effectively balancing brevity with necessary detail.
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?
No output schema. Description covers ordering and notFound behavior but does not detail the full return structure (e.g., which fields each post object contains). While sibling 'get_featurebase_post' may document shape, the tool alone leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds significant meaning: for 'slugs', it explains ordering and error handling; for 'include_content', it clarifies when to enable and the trade-off with excerpt length. This exceeds baseline expectations.
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 action 'Batch-fetch', the resource 'posts', and the method 'by slug array'. It clearly distinguishes from sibling tools like 'get_featurebase_post' (singular) and 'list_featurebase_posts' (likely without slugs).
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?
No explicit when-to-use or alternatives mentioned for tool selection. The 'include_content' parameter provides usage guidance (e.g., 'Off by default — the 800-char excerpt is usually enough... Turn on only when you need the full body'), but overall guidance is minimal.
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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