Acumatica MCP Server

Server Quality Checklist

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Latest release: v0.2.1
Disambiguation5/5
Each tool has a distinct, non-overlapping purpose: CRUD operations, metadata discovery, schema inspection, and action invocation. No two tools could be confused for one another.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., delete_record, describe_entity, list_records). The naming is predictable and uniform.
Tool Count5/5
With 8 tools, the surface is well-scoped for an enterprise resource planning integration. It covers discovery, reading, writing, and actions without being excessive.
Completeness4/5
The tool set provides full CRUD lifecycle (create via upsert, read, update via upsert, delete) plus listing, metadata, schema, and actions. Minor gaps like a dedicated search or bulk operations are absent but tolerable.
Average 4.5/5 across 8 of 8 tools scored. Lowest: 3.8/5.
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 10, 2026
- 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.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must convey behavior. It implies destructive action (delete) and states a requirement. It lacks details on idempotency, return behavior, or permanence of deletion. Output schema exists but is not referenced.
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 concise sentences, front-loaded with the primary action, no extraneous words. Efficiently communicates core function and a usage requirement.
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 simple tool (2 params) and existence of an output schema, the description is adequate but lacks parameter-specific context. It provides a usage requirement but not enough to fully inform an agent without schema descriptions.
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 0%, so description must compensate. It mentions 'ID or key fields' but does not explain how 'key fields' relate to the schema parameters (id, entity). The 'entity' parameter is not clarified at all.
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 (delete) and resource (record), and distinguishes it from siblings which are all non-deletion operations (describe, get, list, upsert, invoke). The mention of 'by ID or key fields' specifies the scope.
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 a prerequisite (ACUMATICA_ALLOW_DELETES=1), giving clear context for use. However, it does not explicitly state when not to use this tool or mention alternatives, though no sibling directly competes.
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 were provided. The description adds context by noting the required environment variable (ACUMATICA_ALLOW_WRITES=1) and explaining HTTP return codes (204 for fire-and-forget, 202 for long-running). However, it does not detail potential side effects, error handling, or reversibility.
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 yet thorough: one sentence for purpose, code examples, then structured argument descriptions. No wasted words, and information is front-loaded.
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 presence of an output schema (not shown) and the complexity of 4 parameters (2 required, 2 optional objects), the description covers purpose, parameters, environment requirement, and return values. It could mention error cases or idempotency but is largely 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?
Schema coverage is 0%, so the description carries full burden. It explains each parameter: entity (entity name), action (use describe_entity to list), entity_record (wrapped format with example), parameters (action-specific). This adds substantial meaning beyond the bare 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 clearly states 'Invoke a named action on an entity' and provides concrete examples (CancelSalesOrder, ReleaseBill), making the purpose unambiguous and distinct from sibling tools like upsert_record or delete_record.
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 explains when to use this tool (invoking actions), mentions using describe_entity to find available actions, and includes examples. It does not explicitly compare to siblings or state when not to use, but the guidance is clear enough for most cases.
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 return format and filter behavior, but does not mention performance, pagination, or authentication requirements. Adequate for a simple read operation.
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 clear sections (Args, Returns, Tip). Every sentence adds value without redundancy, making it easy to parse quickly.
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 simple list tool with one parameter and an existing output schema, the description fully covers purpose, parameter semantics, return structure, and a usage hint. It is complete for its complexity.
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 meaning beyond the schema: it explains the filter is optional, case-insensitive, and provides an example ('order' returns SalesOrder, etc.). This is essential since the schema has 0% description coverage.
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 'List' and resource 'Acumatica entities' and specifies the context 'exposed by this tenant's OpenAPI spec'. It easily distinguishes from siblings like list_records and describe_entity.
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 a tip to call describe_entity for details, guiding usage after listing. However, it does not explicitly mention when not to use this tool or contrast with get_schema, so it's slightly less than perfect.
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?
With no annotations, the description fully discloses the mutation behavior, API pattern, and required environment variable, but omits error handling or idempotency details.
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?
Extremely concise and well-structured: two paragraphs plus a bulleted args list with an example. No wasted 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?
Covers the essential context (prerequisite, API shape, example), but could briefly mention error handling or response format (though output schema may cover response).
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?
Despite 0% schema coverage, the description provides clear parameter explanations and a detailed example for the 'data' parameter, which is critical given its nested object structure.
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 'Create or update a record' and explains the PUT behavior, distinguishing it from read tools like get_record and list_records.
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?
Specifies the prerequisite ACUMATICA_ALLOW_WRITES=1 and explains the create-vs-update logic, but does not explicitly contrast with siblings like delete_record.
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 covers all critical behaviors: warning about incorrect key format causing errors, return structure (status, ok, data/error), browser_url field and its rendering. It also mentions that a GUID works as an alternative key. Fully transparent for the tool's usage.
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 detailed but each sentence adds value. It is structured with a brief summary, then Args section, then Returns. The examples are valuable but could be slightly condensed. 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 existence of an output schema (not shown but known), the description explains the return format comprehensively. It includes error handling, browser_url usage, and prerequisite dependency on describe_entity. Complete for a single-record retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The id parameter is richly explained with examples for different entities and alternative GUID usage. The select/expand/custom are referenced as same as list_records, providing cross-reference. However, entity parameter is not elaborated beyond its name, though it is a known concept from describe_entity. Compensates with practical examples.
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 'Get a single record by its key' and contrasts with list_records by indicating single record retrieval. It clearly distinguishes from sibling tools like delete_record and upsert_record.
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?
It instructs to call describe_entity first to find key_fields and key_format, preventing 500 errors. It also notes that select/expand/custom parameters work similarly to list_records, providing cross-tool consistency. Lacks explicit 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.
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: using non-existent fields causes 500, date/time format requirement, orderby silently ignored, workaround for last-created queries, and the return of browser_url. This is comprehensive and goes beyond basic read-only expectations.
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 well-structured with sections: overview, important callout, args, returns. Every sentence adds value, though it could be slightly more concise without losing critical detail.
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 (8 parameters, OData syntax, error-prone behaviors, and pagination), the description is thorough. It covers prerequisites, edge cases, return format (including error structure and browser_url), and even provides a step-by-step workaround for a common query pattern. Output schema exists but the description adds value beyond it.
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 description coverage is 0%, so the description must compensate. It extensively documents each parameter: filter format with examples, top default and exploration tip, skip for pagination, select/expand based on describe_entity, orderby caveat with workaround, and custom fields format. This adds significant meaning 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 clearly states 'Retrieve records from an Acumatica entity using OData query parameters.' with a specific verb ('retrieve') and resource ('records from an entity'). Among siblings like get_record, delete_record, etc., it is distinct as the list operation.
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 explicitly instructs 'Call describe_entity(entity) first to get the exact field names' and explains why (avoid 500 errors). It provides context for proper usage but does not explicitly mention when not to use this tool or compare with alternatives like get_record.
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: two return shapes for normal vs query-only entities, error response for unknown entities, and concrete examples. It also notes that query-only entities have no addressable key.
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: a one-line summary, usage instructions, Args section, and two return shapes with examples. It is front-loaded with the main purpose. Some redundancy could be trimmed, but overall clear.
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 (different handling for normal vs query-only entities) and the presence of an output schema, the description provides complete contextual information: when to use, what to expect, and edge cases. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'entity' has 0% schema coverage, but the description adds value by specifying it as the entity name with examples (e.g., 'SalesOrder'). While sufficient for a simple parameter, the examples are helpful but not exhaustive.
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 returns full metadata for an entity including fields, key format, actions, and sub-collections. It distinguishes itself from siblings like list_entities by specifying the exact information provided.
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 advises calling this tool before list_records or get_record when uncertain about field names, id format, or expand parameters. It also differentiates between normal and query-only entities, warns against calling get_record on query-only entities, and mentions HTTP 500 risks without filters.
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 carries the behavioral transparency burden. It explains the response structure (nested under view names), mentions that standard DAC fields absent from the contract can still be pulled via custom=, and provides common view names. 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 bullet points and an example, and is front-loaded with the purpose. It is slightly verbose but every part adds value. Could be slightly more concise, but still effective.
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 existence of an output schema, the description does not need to explain return values. It is complete for the tool's purpose, covering what it returns, why to use it, and how to use the results with other tools like list_records.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'entity' has no schema description coverage, but the description adds meaning by giving usage context, examples (e.g., 'SalesOrder'), and explaining that it is the entity name. It adds value beyond 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 clearly states that the tool returns the entity's extension-field schema, and distinguishes it from siblings like describe_entity and list_records by explaining it discovers user-defined fields and view names not in the standard contract.
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 explicitly lists two reasons to call the tool and provides an example workflow. It also implicitly tells when not to use it (e.g., for standard contract fields, use describe_entity) and mentions alternatives like describe_entity().
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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