festo-codesys-mcp

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation4/5
Most tools have distinct purposes: review_st_code for validation, explain_error_code for error decoding, plc_library for library access, st_symbols for symbol navigation, st_find_references for reference finding. However, plc_lookup overlaps with explain_error_code by also decoding error codes, though descriptions differentiate them as quick lookup vs. comprehensive search.
Naming Consistency3/5
Tool names use snake_case but follow inconsistent patterns: some start with verbs (review_st_code, explain_error_code), others with nouns (plc_library, plc_lookup, st_symbols) or a verb phrase (st_find_references). This mix reduces predictability.
Tool Count5/5
With 6 tools for PLC development, the set is well-scoped. Each tool addresses a clear need: code validation, error handling, library access, quick lookup, symbol navigation, and reference finding. No tool is redundant.
Completeness5/5
The tool set covers the essential tasks for ST coding assistance: code style validation, error code resolution, reusable block library, quick references, project navigation, and refactoring support. There are no obvious gaps for the intended use case.
Average 4.4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 14 commits in the last 12 weeks
- Last stable release on July 17, 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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations by noting 'instant answers without loading full knowledge topics', which implies no side effects and fast response. Annotations already indicate readOnly, idempotent, non-destructive behavior, and the description complements this well without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured with a clear 'USE WHEN' block and action list. Every sentence adds value, and it is front-loaded with the tool's 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 output schema exists, the description does not need to detail return values. It covers usage context and actions comprehensively. Minor gap: no mention of error handling for invalid lookup values.
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 documents both parameters well. The description lists actions but does not add significant new meaning beyond what is in the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: quick lookup for PLC conventions and error codes. It lists specific actions, which helps distinguish from siblings, though it does not explicitly differentiate from all listed sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage guidance: 'USE WHEN: you need a single fact' and suggests trying this tool before a related tool (plc_knowledge) for point lookups. However, it does not mention when not to use it relative to the listed sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description claims the tool saves findings to knowledge/manuals for future use, implying a write operation. However, annotations declare readOnlyHint=true, indicating no state modification. This is a direct contradiction, significantly reducing 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 concise, with front-loaded main purpose. Every sentence adds value without redundancy, achieving clarity in few 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 tool's complexity (multi-platform error decoding), the description covers input formats, search sources, fallback web search, and saving behavior. With an output schema present and thorough annotations, this is comprehensive.
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. Description adds value by explaining acceptable input formats for errorCode (hex, IEC, decimal) and describing search sources (CiA 402, Festo PtP, etc.), which enriches the meaning of both parameters.
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 decodes Festo/CODESYS/EtherCAT error codes using all embedded references. It specifies the verb 'decode' and resource 'error codes', distinguishing it from sibling tools like review_st_code or plc_lookup.
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 'USE WHEN: any Festo/CODESYS/EtherCAT error code appears' with examples like 0x..., 16#..., drive fault, AL status. It also warns against guessing, providing clear usage context.
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?
Annotations already show read-only, idempotent, non-destructive. Description adds value: returns only violations, not reference dumps, includes quick-reference table. No contradiction.
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?
Succinct multi-line description with front-loaded purpose and bullet-like list of checks. Some redundancy (e.g., 'immediately after writing' could be concise).
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?
Simple tool with one input and no output schema; description covers purpose, usage, checks, and output behavior. Could clarify what happens with no violations (likely empty result) but sufficient.
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?
Parameter 'code' is fully described in schema (100% coverage). Description adds no extra parameter depth beyond the schema's own 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?
Description clearly states it validates ST code against naming conventions and lists specific checks (Hungarian notation, POU prefixes, etc.), distinguishing it from siblings like explain_error_code or st_find_references.
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?
Explicit 'USE WHEN: immediately after writing or editing any ST code' provides clear context. Does not explicitly mention when not to use or alternatives, but the sibling list is provided separately.
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?
Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds value by detailing the actions (search, list, get) and that it provides source code, without contradicting 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 reasonably concise and front-loaded with the main purpose. Each sentence adds value, though it could be slightly more compact.
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 4 parameters with enums, rich annotations, and no output schema, the description covers actions, categories, usage guidance, and what to expect, making it fully informative for the agent.
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 has 100% coverage. Description adds examples (e.g., 'FB_StandardMotor' for name) and explains the actions and categories in more detail than schema, enhancing 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 'Access the 38-block reusable ST library' and lists specific actions (search, list, get) and categories. This distinguishes it from sibling tools like 'review_st_code' and 'plc_lookup'.
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?
Explicit guidance: 'ALWAYS check here BEFORE creating new FBs' and 'DO NOT create a new FB if a similar one already exists.' It lacks explicit alternatives, but the context strongly implies when to use.
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?
The description adds rich behavioral context beyond the annotations (readOnlyHint, idempotentHint, destructiveHint). It details token-awareness, ignoring comments/strings/substrings, and specifies the output fields (file, line/col, line text, containing POU, declaration flag, disambiguation hints). It also notes the workspace constraint for sourceDir.
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 extremely concise at 3 sentences, with a clear 'USE WHEN' callout and a final note on workspace restrictions. No wasted words, front-loaded with the main purpose.
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 (4 parameters, full schema coverage, existing output schema, rich annotations), the description covers all necessary aspects: behavior, usage context, constraints, and output details. It is complete without needing to repeat output schema information.
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 covers all 4 parameters with descriptions (100% coverage). The description does not add new parameter-specific semantic details beyond the schema; it provides tool-level context but no extra per-parameter elaboration. Baseline 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 verb and resource: 'Find all references (usages) of an ST identifier across a directory of .st files'. It distinguishes itself from grep by being token-aware and safe, and differentiates from sibling tools like plc_lookup or st_symbols by focusing on references for renaming/refactoring.
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 an explicit 'USE WHEN' statement: 'USE WHEN: you need every usage of an ST identifier across files before renaming or refactoring.' This provides clear context for when to use the tool, though it does not explicitly state when not to use it or name specific alternatives.
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?
Annotations already declare readOnly, idempotent, non-destructive. The description adds valuable behavioral context: dialect-aware (CODESYS V3.5), comment/string-safe, workspace restriction with env var override, and return format (file + container). No contradictions.
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 well-structured with sections, bullet points, and clear language. It is somewhat lengthy but every sentence adds value. Could be slightly more concise, but overall efficient for the information provided.
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 presence of an output schema, the description appropriately focuses on usage and constraints. It covers workspace restrictions, different actions, and explicitly mentions limitations (no line numbers/find-references). The description is complete for an agent to use the 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 description coverage is 100%, so each parameter is documented. The description adds actionable nuance: explains default behavior of outline (top-level symbols) and how kindFilter extends it, and notes that definition is case-insensitive. This adds 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 uses specific verbs ('index', 'navigate') and clearly distinguishes the tool from siblings by noting it is dialect-aware and better than grep. It explicitly mentions the two actions and the resource (.st files).
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 'USE WHEN' guidance: to navigate an existing .st project for outlining or resolving definitions. It also clarifies what the tool does NOT do (line numbers, find-references), directing agents to future updates or other tools.
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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