custom-mcp-server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: annotation_status for task status, dynamo_read/write for database, s3_download/upload for storage, slack_notify for messaging. No overlap.
Naming Consistency4/5
Most tools follow verb_noun pattern (dynamo_read, dynamo_write, s3_download, s3_upload, slack_notify), but 'annotation_status' is an outlier as a noun phrase.
Tool Count5/5
6 tools is well-scoped for a server covering annotation, database, storage, and Slack integration. It feels neither too few nor too many.
Completeness3/5
Each service has basic operations but lacks deletions, updates, and lists. For annotation only status is provided. This leaves notable gaps for typical workflows, but the server may be intentionally scoped.
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
- 7 commits 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
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
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  ]
}
```
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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?
With no annotations, the description must disclose behavioral traits. It mentions keying by id but omits critical details such as the overwrite parameter's effect (default true) and failure behavior when overwrite is false. No side effects or consistency guarantees are described.
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, short sentence that is to the point. It achieves conciseness but could be improved by including more context without sacrificing brevity.
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 no output schema, three parameters (including a nested object), and no annotations, the description is incomplete. It does not explain return values, error behavior, or what happens on duplicate ids.
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 the schema already adequately describes all three parameters. The description adds 'keyed by id' which is redundant with the schema's primary key description, providing no additional meaning.
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 verb 'Write' and the resource 'a record to DynamoDB keyed by id', distinguishing it from sibling dynamo_read. However, it does not mention the overwrite behavior or additional attributes.
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 like dynamo_read or s3_upload. There are no explicit when-not or context clues.
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. The description implies a write operation but omits important behavior: overwrite semantics, permission requirements, error handling, or side effects like triggering bucket events. The base64 overhead and potential size limits are not mentioned.
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 with no wasted words. It is front-loaded with the action and resource. Slightly more detail could be added without sacrificing 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 no output schema and no annotations, the description should provide more context about the return value, default bucket behavior, and MIME type handling. It lacks completeness for a tool with four parameters.
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 the baseline is 3. The description adds no additional meaning beyond the parameter names and types already in the schema. It does not clarify the relationship between 'key' and 'bucket' or the necessity of valid base64 in 'contentBase64'.
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 ('Upload'), the resource ('object to S3'), and the encoding requirement ('base64-encoded'). It distinguishes from the sibling tool s3_download, which downloads objects.
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, prerequisites (e.g., AWS credentials), or constraints (e.g., object size limits). The description does not contrast with s3_download or other 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that the output is base64-encoded, which is key behavior, but does not mention limitations (e.g., file size, timeout), permissions required, or whether the tool is safe/read-only. The description adds some value beyond the schema but is insufficient for a no-annotation tool.
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 sentence that conveys the essential purpose and key detail (base64 encoding). No extraneous information. Efficient and well-structured.
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 has 2 parameters, no output schema, and no annotations, the description is minimal but covers the core functionality. However, it lacks details on error handling, default bucket behavior, or size limits. For a simple download tool, it is 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?
The input schema provides descriptions for both parameters ('key' and 'bucket') with 100% coverage. The description does not add new meaning beyond the schema; it only restates the purpose. 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 explicitly states 'Download an object from S3 and return it base64-encoded', which is a specific verb ('download'), resource ('S3 object'), and adds detail about encoding. This clearly distinguishes it from sibling tools like s3_upload (upload) and other non-S3 tools.
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. For example, it does not mention that this is for small objects due to base64 encoding, or contrast with other data access tools like dynamo_read. The description lacks context for when this tool is appropriate.
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 must fully disclose behavior. It indicates read or update, but omits details like required permissions, whether reading requires no updates, side effects of Slack notification (e.g., which channel is used), and if the operation is idempotent.
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, clear sentence with no unnecessary words. Front-loads the core purpose (read or update) and optional feature.
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 exists, so the description should indicate what the tool returns (e.g., updated status or current status). It fails to do so, leaving the response behavior ambiguous. However, it covers the core functionality adequately.
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 description adds no new parameter meaning beyond the structured fields. The mention of 'optionally notifying Slack' aligns with the notify parameter's 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 clearly states the tool reads or updates an annotation task's status, with optional Slack notification. It distinguishes from sibling tools like dynamo_read/write by focusing on annotation status, and from slack_notify by combining status update with notification.
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 annotation status operations but does not explicitly state when to use this tool over siblings (e.g., dynamo_read/write for generic data, slack_notify for standalone notifications). No when-not-to-use guidance provided.
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 fully convey behavioral traits. It only states the basic action without mentioning authentication requirements, rate limits, whether messages are formatted, or error behavior. This is insufficient for an agent to understand side effects or constraints.
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, concise sentence that front-loads the action and resource. Every word is necessary and there is no wasted text.
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 absence of an output schema and annotations, the description is minimal. It covers the core purpose but lacks details on limitations (e.g., message length), return values, or confirmation of success. It is adequate for a simple tool 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 schema already documents each parameter (message, channel, threadTs) with descriptions. The tool description adds no additional meaning beyond what is in the schema, so a baseline score of 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 action ('Post a message') and the resource ('to a Slack channel'). It is a specific verb+resource pair that distinguishes this tool from siblings like dynamo_read or s3_upload, which operate on different services.
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 does not provide explicit guidance on when to use this tool versus alternatives. While the siblings are dissimilar, there is no mention of prerequisites or context (e.g., 'use this to send notifications, not for file uploads'). Usage is implied but not clarified.
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 full burden. It discloses the tool is read-only (non-destructive) but does not mention any behavioral traits like rate limits, consistency modes beyond the parameter, or error handling. The description is minimal but not contradictory.
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?
A single sentence that is concise and front-loaded with the verb 'Read'. Every word serves a purpose, no fluff.
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?
For a simple tool with two parameters and no output schema, the description covers the essential purpose and key. Could optionally mention the return format, but it's not required for a straightforward read operation.
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 both parameters documented. The description adds 'by primary key id' which matches the schema, but does not add new meaning beyond what the schema provides. 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 'Read a single record from DynamoDB by primary key id', which specifies the verb (read), resource (DynamoDB record), and the unique key. This distinguishes it from sibling tools like dynamo_write (write) and s3_download (different service).
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 when you have a specific 'id' to retrieve a single record. It does not explicitly state when not to use (e.g., for batch reads) but the purpose is clear enough for basic selection.
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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