DiscoMCP

by ieranama

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a distinct role in the profiling lifecycle: executing probes, finalizing profiles, inspecting targets, etc. No two tools overlap in purpose.
Naming Consistency4/5
Six of seven tools follow the verb_noun pattern (execute_probe, finalize_profile, generate_skill, inspect_target, list_targets, lookup_target). Only session_status deviates with a noun_noun format.
Tool Count5/5
Seven tools cover the entire profiling workflow from target discovery to skill generation without being excessive. Each tool serves a necessary step.
Completeness4/5
The tool set covers the core profiling operations but lacks profile management features like deletion or session cancellation, which are minor gaps.
Average 3.8/5 across 7 of 7 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 43 commits in the last 12 weeks
- Last stable release on July 13, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
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 provided, so the description must fully disclose behavioral traits. It only says 'regenerate' which implies creation/overwriting, but does not specify side effects, idempotency, required permissions, or output behavior.
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 includes necessary details (the files involved). It is efficient with no redundancy, though could be slightly more structured (e.g., using bullet points for the file list).
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 tool with only one parameter and no output schema, the description covers the basic purpose and input. However, it lacks details on return values, error conditions, dependencies (e.g., that the directory must contain those files), and behavioral guarantees.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The lone parameter 'profile_dir' is described only as a 'profile directory' in the description, with no format, path syntax, or constraints. Schema description coverage is 0%, so the description adds minimal meaning beyond the parameter name.
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 ('Regenerate SKILL.md') and the resource ('from an existing profile directory'), listing the exact files involved. It is distinct from sibling tools which focus on probing, finalization, inspection, listing, lookup, and session status.
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, nor does it mention prerequisites, when not to use it, or any context for selecting it over sibling tools.
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 exist, so description carries full burden. It discloses the main actions (connect, list, start profiling) and that it returns tool cards for risk classification, but does not explain side effects (e.g., network calls, state changes), safety, or idempotency.
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?
Two sentences front-loading the main action. The second sentence adds a useful instruction about risk classification. Could be slightly more structured but is appropriately concise.
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?
Covers the main actions and output format adequately, but lacks details about the profiling session workflow, error handling, prerequisites for connecting to a target, and how it fits with sibling tools. Without an output schema, the description provides a text explanation of the return format, which is helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 50% description coverage (only 'goal' is described). The description does not add meaning to 'target' or elaborate on parameter usage beyond what is in the schema. 'Target' remains undocumented.
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 verb 'Connect', 'list', and 'start', and the resource 'target MCP' and its declared tools/resources/prompts. Distinguishes from siblings like list_targets (which lists targets) and lookup_target (looks up a specific target) by being the tool that initiates a profiling session.
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 explicit guidance on when to use this tool versus alternatives like execute_probe or finalize_profile. The description does not mention prerequisites, context of use, or 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states it does not make target calls or consume probes, and clarifies it reports but does not decide. It details exactly what the report contains. With no annotations, this provides good behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single moderate-length paragraph that front-loads the main purpose and efficiently lists report components. Minor clutter from parenthetical details, but overall 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?
The description thoroughly explains all report components despite no output schema. However, the missing definition for the 'target' parameter leaves a significant gap for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has one required parameter 'target' with no description in schema (0% coverage). The tool description does not explain what 'target' means or how to use it, failing to add the necessary semantic value.
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 it returns a 'GAP REPORT' for an active session, listing specific components (unsampled_structures, unexecuted_tools, etc.). It distinguishes from siblings like execute_probe and finalize_profile by emphasizing it does not make target calls or consume probes.
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 safe usage ('no target calls, no probe consumed') and notes the report is also returned with every execute_probe result, but does not explicitly state when to call this tool standalone versus relying on the attached report. No alternatives or exclusions 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?
The description implies a read-only operation but does not explicitly state behavioral traits like idempotency, speed, or authorization needs. Without annotations, the description carries the full burden; it is accurate but minimal.
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, front-loaded sentence with no wasted words. It could be slightly more informative but remains concise.
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 (no parameters, no output schema), the description is minimally adequate. However, it does not mention return format or potential use context, leaving room for improvement.
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?
No parameters are defined, and schema coverage is 100%. The description does not need to add parameter information; baseline score of 4 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 lists target MCP IDs, using a specific verb and resource. It distinguishes from siblings like 'inspect_target' or 'lookup_target', which likely provide more detail.
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. There is no mention of use cases, prerequisites, or relationships to sibling tools like 'inspect_target'.
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 are provided, so description carries burden. It discloses writing to disk, verification steps, anti-fabrication checks, and stub behavior for zero probes. Lacks mention of idempotency or potential side effects but is otherwise transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long and includes imperative warnings that are important but could be condensed. It front-loads the main purpose, then adds constraints. Some redundancy exists in the verification phrasing.
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 complexity and lack of output schema, description covers essential conditions (zero probes, verification, return of skill_path). It could detail the return format further but is sufficiently complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%; only usage_summary has a description in schema. The tool description adds meaning for usage_summary but does not explain the 'target' parameter at all, leaving agents unclear about its role.
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 synthesizes workspace model, operational model, capability profile, quality report, and SKILL.md from safe observations and writes them to disk. It distinguishes from siblings like generate_skill by specifying the full artifact set and finalization aspect.
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?
Description provides context for when to use: after accumulated safe observations, with verification requirements. It also covers the zero-probes edge case. However, it does not explicitly list alternative tools or when not to use this tool.
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?
Despite no annotations, the description fully discloses behavior: it is a read-only check that does not probe, and on MISS it triggers background profiling while allowing the user's task to continue. This goes beyond basic disclosure.
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?
Two sentences with no filler, efficiently packing purpose, behavioral constraints, and conditional workflow in a clear, front-loaded manner.
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?
The description covers the main purpose and flow, but omits explicit mention of return values (e.g., what does a HIT look like?) and error handling. However, given the tool's nature and sibling context, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not elaborate on the 'target' parameter beyond implying it is the target of interest. It does not specify format, constraints, or examples, so the description adds little value over the raw 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 uses a specific verb ('Check whether') and resource ('DiscoMCP skill... covers this target') and distinguishes itself from the probing sibling tools by explicitly stating 'without probing' and referencing the alternative workflow (inspect_target, execute_probe).
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 when-to-use guidance: use this tool to check coverage to avoid unnecessary probing. It also tells what to do on a MISS (dispatch background subagent) and maintains user task continuity, clearly differentiating from full probing tools.
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 provided, the description fully discloses behavioral traits: validation, execution conditions, classification advisory, provenance checking, anti-fabrication, budget enforcement, return values (redacted observation or rejection reason), and gaps report. There is no contradiction with missing annotations.
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 lengthy but packed with essential information for a complex tool. It front-loads the purpose and then systematically explains behavioral rules. Could be slightly more concise, but the density of information justifies the length.
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?
Given the tool's complexity (6 parameters, nested objects, no output schema), the description is remarkably complete. It explains all behaviors, return values, and edge cases (rejection reasons, gaps report). There are no obvious gaps.
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 description coverage is 83%, which is high, but the description adds significant value beyond the schema by explaining the advisory nature of classification, provenance checking rules, and the meaning of gaps report. It helps the agent understand parameter semantics more fully.
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's purpose: 'Validate and, if permitted, execute ONE tool call against the target.' It specifies it is for probe execution, distinguishing it from sibling tools like inspect_target or list_targets which serve different functions. The verb 'execute' and resource 'probe' are explicit.
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 detailed usage guidelines: 'DEFAULT-DENY' policy, conditions for a probe to run (read-only provability), classification advisory, provenance requirements, and budget enforcement. It explicitly contrasts with destructive tools and tells when not to use. This is comprehensive guidance.
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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