synthlab-mcp

by j0KZ

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Server Quality Checklist

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Latest release: v0.9.1
Disambiguation3/5
Some tools have overlapping purposes, e.g., analyze_patch, parse_patch, and validate_patch all deal with parsing/validating .pd files; compose_patch, create_from_template, and generate_patch all generate patches. Descriptions help distinguish but could still cause misselection.
Naming Consistency5/5
All tool names consistently use lowercase with underscores and follow a verb_noun pattern (e.g., analyze_patch, generate_vcv, send_message). Even create_from_template is clear and predictable.
Tool Count5/5
10 tools is well-scoped for the domain of Pd and VCV Rack patch management, covering creation, analysis, validation, and control without being excessive.
Completeness4/5
The tool set covers the primary workflows: patch generation (via multiple methods), analysis/validation, and real-time control. Minor gaps like explicit update/delete or VCV analysis exist, but agents can work around them.
Average 4.4/5 across 10 of 10 tools scored. Lowest: 3.6/5.
See the Tool Scores section below for per-tool breakdowns.
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This repository includes a README.md file.
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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 behavior. It states the tool parses and returns a structured description but does not clarify side effects (e.g., non-destructive reads, file system access, or error handling).
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 without waste, but could benefit from specifying output format or error cases. Still, it is appropriately sized for the tool's simplicity.
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 has one parameter, no output schema, and no annotations, the description adequately covers the purpose and output structure. It does not mention validation or error conditions, but these are minor 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?
The description adds significant value beyond the schema by explaining that 'source' can be either a file path or raw .pd text, with a specific heuristic for detection (starts with '#N canvas'). Schema coverage is 100%, and the description enhances 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 verb 'parse', the resource 'Pure Data .pd file', and the specific outputs ('objects, connections, and signal flow'). It distinguishes itself from siblings like 'analyze_patch' which implies analysis rather than parsing.
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 (e.g., 'analyze_patch' or 'validate_patch'). The description lacks context for selection or exclusion criteria.
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 the structural checks performed and implies read-only validation. Lacks details on failure behavior or side effects, but adequate for a validation 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?
Single sentence covering purpose and scope. Front-loaded with action and subject, 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?
No output schema and no mention of return value format. For a validation tool, knowing what is returned (list of issues, boolean, etc.) is important. Parameter description is adequate.
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 100%; description almost repeats schema description. Adds minimal extra value beyond what the schema already provides for the single parameter.
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 verb 'validate' and specific resource 'Pure Data .pd file', listing exact checks (broken connections, orphan objects, etc.). Distinguishes from siblings like parse_patch or compose_patch.
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?
Implied usage for validation but no explicit when-to-use, when-not-to-use, or alternative references. Agent must infer context from tool name and siblings.
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 must carry the burden. It lists what the tool produces, but does not disclose side effects, authentication needs, or performance implications. As a read-only analysis, the lack of side effects is inferred, but not stated.
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 effectively lists the tool's capabilities without extraneous words. It is front-loaded with the main purpose.
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 single parameter and no output schema, the description adequately covers what the tool does. However, it could mention that the output is a structured result, but since no output schema exists, the description itself is reasonably complete.
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?
The description adds significant value beyond the schema by specifying that if the source starts with '#N canvas', it is treated as raw text. This clarifies the dual nature of the parameter. Schema coverage is 100%, so baseline is 3, but the added context pushes it to 5.
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 'Analyze' and resource 'Pure Data .pd file', and enumerates specific outputs (object counts, signal flow graph, DSP chain, complexity scoring, validation). This differentiates it from sibling tools like validate_patch, which likely only validates.
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 guidance on when to use this tool instead of parse_patch or validate_patch. The description implies comprehensive analysis, but does not directly state when it is preferable.
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 description carries burden. It warns against post-tool shell operations but does not disclose side effects like file overwriting when outputPath is given, error handling, or permissions needed.
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?
Description is four sentences, front-loaded with purpose, and each sentence adds necessary guidance. Could be slightly more concise but no unnecessary words.
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 and lack of output schema, the description covers key aspects: always returns content, how to handle it, post-tool warnings, and parameter special cases. Lacks error handling details but schema covers validation.
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%, so baseline is 3. The description adds value by clarifying that outputPath should only be used when user explicitly requests it, and provides special arg formatting for message boxes, going beyond 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 it generates a valid Pure Data .pd file from a JSON specification, distinguishing it from sibling tools like analyze_patch or validate_patch.
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?
Provides explicit instructions to present the returned content directly to the user, stop after presenting, and avoids any shell operations. Also gives specific formatting advice for message boxes. Lacks mention of when not to use, but coverage is strong.
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 bears full responsibility. It discloses that files are written to disk if outputDir is provided, that content is always returned, and warns against post-tool file operations. It could mention overwriting behavior, but overall transparent.
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 moderately long but well-structured: main action first, then details on modules, wiring, controller, outputDir, and critical imperatives. Each sentence adds value; minimal redundancy.
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 complex tool with 4 parameters, nested objects, and no output schema, the description fully covers all aspects: purpose, parameter details, return behavior, and safety instructions. No gaps for agent decision-making.
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%, so baseline is 3. The description adds significant value beyond schema: explains wiring connections, controller auto-mapping, and outputDir behavior, making parameters more actionable.
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 generates an entire Eurorack-style rack of Pd patches, listing specific outputs (individual .pd files and combined _rack.pd) and optional components (wiring, controller). It distinguishes from sibling tools like create_from_template by being a bulk generation tool.
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 includes explicit instructions on how to handle the output (present content to user, stop, avoid file operations), and outlines when to use wiring and controller config. While it doesn't explicitly compare to alternatives, the usage context is clear.
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?
Discloses key behaviors: returns complete .pd content, handles everything internally, and warns against extra commands. With no annotations, description carries full burden; it effectively communicates the tool's safety and output expectations, though could be more explicit about default file creation.
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?
Well-structured with purpose first, then templates, then behavioral instructions. Every sentence contributes, but length could be reduced slightly without losing clarity. Still, it's efficient for the complexity.
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?
Covers template options, parameter details, output behavior (content always returned), and optional writing. No output schema, but description compensates by explaining the response content. Lacks error handling details but sufficient for agent invocation.
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%, but description adds significant value by listing template-specific parameter examples (e.g., synth: waveform, filter; drum-machine: voices, morphX, morphY) with exact formats, going well beyond the schema's brief 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?
Clearly states it generates a Pd patch from a parameterized template, lists 11 specific templates, and distinguishes from sibling tools like analyze_patch, validate_patch, and send_message. The verb 'Generate' and resource 'Pd patch' are specific.
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?
Explicitly instructs when to use (for template-based patches) and when not to (no file/shell operations after). Provides a clear STOP message and alternatives (e.g., optional outputPath only if user requests). 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses what information returns in each mode (module slugs, tags, HP widths vs. I/O port names, param names). No annotations exist, so description carries full burden. It doesn't mention error handling or rate limits, but the read-only nature is implied.
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?
Description is informative but slightly verbose. It front-loads the action and uses clear instructions. Could be slightly trimmed, but still efficient for the information conveyed.
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 2 parameters, 100% schema coverage, and no output schema, description adequately covers modes and supported plugins. Lacks explicit return format or error handling, but is sufficient for typical use. Sibling tools context reinforces need for lookup.
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?
Adds value beyond schema by explaining plugin aliases (e.g., 'mi' for Mutable Instruments) and that module parameter is a slug. Clarifies that omitting module lists all modules. Schema already covers param descriptions, but description enriches usage 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?
Description specifies 'List available VCV Rack modules and their ports/params for a given plugin' and distinguishes two modes (with/without module). This clearly identifies the tool's purpose and differentiates it from siblings like generate_vcv.
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?
Explicitly states 'ALWAYS call this BEFORE generate_vcv to look up correct module slugs and port names — do NOT guess.' Also lists supported plugins, providing clear guidance on when to use and prerequisites.
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?
No annotations provided, but the description fully discloses behavior: auto-selects templates per role, always returns .pd content in response, warns against shell/file operations, and explains outputDir's role. Contradiction false.
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?
Well-structured with main purpose first, then prerequisites, enumerated values, and critical warnings. Slightly verbose but every sentence is informative. Front-loads key info.
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 8 parameters, nested objects, and no output schema, the description covers all necessary aspects: prerequisites, value ranges, output handling, and post-call actions. An agent can use this tool correctly.
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%, baseline 3. The description adds value by listing all possible values for genre, mood, roles, and explaining template selection logic, going beyond 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?
Clearly states it composes a complete Pd patch from a high-level description. Distinguishes from sibling tools like analyze_patch or generate_vcv by focusing on high-level composition with genre, mood, instruments, etc.
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?
Explicitly instructs to first gather user info about genre, mood, tempo, etc., and only call once enough info is gathered. Also tells to present results as code blocks and avoid file operations, providing clear when-to-use and not-to-use guidance.
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 behavior: it explains that the complete .vcv content is always returned, instructs the agent to present it directly and stop, and warns against any file/shell operations. It also clarifies the outputPath parameter is optional.
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 efficiently structured: purpose, important usage note, list of supported plugins, and explicit post-call instructions. Every sentence earns its place without unnecessary repetition.
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 complexity of generating a patch file, the description covers all necessary context: what it does, prerequisites, supported plugins, output behavior, and what to avoid after. No output schema is present, but the description clearly explains the returned content.
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 detailed descriptions for each parameter. The description adds value by providing usage context (e.g., using list_vcv_modules for correct slugs) and guidance on optional outputPath. It does not repeat schema info but adds operational semantics.
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 that the tool generates a VCV Rack .vcv patch file from a JSON specification, using a registry of module port/param IDs. It clearly distinguishes itself from sibling tools by instructing users to use list_vcv_modules first.
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 list_vcv_modules first to look up exact module slugs and port names — do NOT guess.' It also lists supported plugins and gives post-call instructions (do not run file operations).
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 bears the burden. It discloses that confirmation is always returned and cautions against additional file operations, accurately indicating the tool's side effects and 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, well-structured paragraph that front-loads purpose, then covers prerequisites, examples, and warnings. Every sentence is informative, with no wasted words.
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 5 parameters, no output schema, and no annotations, the description thoroughly covers prerequisites, usage examples, important behavior, and parameter hints, making it complete for effective use.
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 value with common address examples, default port explanations, and argument types, going beyond what the schema provides.
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 'Send a control message to a running Pure Data instance via OSC (UDP) or FUDI (TCP).' It identifies the specific verb (send), resource (control message to Pd), and distinguishes from sibling tools like create_from_template or compose_patch.
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?
Explicitly states prerequisite: 'Requires a bridge patch loaded in Pd — use create_from_template with template "bridge" to generate one.' Also warns against additional file operations after calling, providing clear when-to-use and when-not-to-use 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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