Accounting Ledger MCP Server

by dougdaley

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: setup, reporting, and four specific transaction types. The echo tool is unrelated but not confusing, as it serves a generic utility function.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern with snake_case (create_ledger, generate_profit_loss_report, record_*). The exception is 'echo', which is a simple verb, but this is a minor deviation.
Tool Count5/5
Seven tools is well-scoped for an accounting ledger server: one setup tool, four transaction recording tools, one reporting tool, and one utility. Each tool earns its place.
Completeness3/5
The server covers setup, transaction recording, and reporting, but lacks fundamental operations like listing or retrieving transactions, editing, or deleting records. This creates a gap where agents cannot inspect or manage recorded data directly.
Average 3.6/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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 carries the full burden. It only states what the tool does ('Records a cash purchase') without disclosing side effects, required permissions, error conditions, or what happens after recording. For a mutation tool, this is a significant gap.
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 and well-structured: a one-sentence purpose followed by an Args list. Every line adds value, with no wasted words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite good parameter coverage, the description lacks usage guidelines and behavioral transparency. With no output schema or annotations, the tool is underspecified—users are left unsure about when to use it versus siblings and what happens on execution.
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 description compensates for the schema's 0% coverage by providing brief but meaningful descriptions for all parameters, e.g., 'amount: Purchase amount (excluding tax)' and 'tax_code: Tax code to apply (default: GSTIN)'. However, it does not elaborate on allowed tax codes or the role of entity_name.
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 states 'Records a cash purchase (expense) transaction,' which clearly identifies the action and resource. It distinguishes from sibling tools like record_cash_sale by specifying 'cash purchase' and 'expense,' though it does not explicitly reference alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like record_supplier_bill or record_client_invoice. The description implies cash purchases but does not discuss exclusions, prerequisites, or context.
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?
With no annotations, the description must disclose behavior. It honestly lists side effects (creating engine, migrating schema, inserting defaults) and notes the 'if not present' condition. However, it does not cover potential risks like destructive migrations, required permissions, or reversibility, leaving transparency gaps.
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 compact three-item bullet list, front-loaded with the purpose statement. Every line adds concrete action information, and there is no redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the small surface area (one parameter, no output schema), the description is incomplete because it ignores the only required parameter, which is essential for invocation. It also doesn't address return values or prerequisites, leaving the agent without a full picture of how to use the tool correctly.
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?
The schema has one required parameter `entity_name` with zero description coverage, and the tool description does not mention it at all. This is critical: an agent cannot infer what `entity_name` represents (e.g., the ledger name, the default reporting entity's name) or its format. The description fails to compensate for the lack of 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 the tool's purpose as setting up the ledger, listing specific actions: creating the SQLAlchemy engine, running migrations, and creating default entities. This distinguishes it from sibling tools that record transactions or generate reports.
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?
While the description implies the tool is for initial ledger setup, it does not explicitly state when to use it versus alternatives, nor does it provide exclusions or prerequisites. The mention of defaults 'if not present' hints at idempotent setup but lacks clear guidance such as 'run before other 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?
With no annotations present, the description carries the full burden of behavioral disclosure. It only states that it records a transaction, without mentioning side effects, required permissions, tax calculations, or whether a ledger entry is created. This minimal disclosure leaves significant behavioral ambiguity.
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 compact and well-structured, with a one-sentence purpose statement followed by a clean Args list. Every line is informative, with no redundant text or filler.
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 simple tool with 5 parameters and no output schema, the description is adequate for basic invocation. However, it lacks usage context, such as typical scenarios or relationship to accounting workflow, and doesn't explain return values or error conditions. It is minimally complete but not rich.
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 schema provides no parameter descriptions (0% coverage), but the description compensates by listing each argument with meaning: amount is 'excluding tax', tax_code has a default, and entity_name is described. This adds value beyond the schema's bare property names.
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 'Records a cash sale transaction' with a specific verb and resource. The term 'cash sale' distinguishes it from sibling tools like record_cash_purchase, record_client_invoice, and record_supplier_bill, making its purpose unambiguous.
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. It does not mention scenarios, prerequisites, or edge cases (e.g., when to use a cash sale instead of an invoice). Sibling names imply differences, but the description itself offers no explicit usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions that the report is returned as a JSON string but does not disclose whether the operation is read-only, whether existing ledger data is required, or any constraints or side effects. For a tool that may depend on prior recorded entries, this is a notable gap.
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 and well-structured with a one-line summary followed by a clear Args/Returns layout. Every sentence adds value and there is no redundancy or irrelevant information.
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 covers the core purpose and parameters but leaves gaps: it does not mention default behavior when dates are omitted, that entity_name defaults to 'Example Company', or what happens if no financial records exist. It also lacks an output schema, so the return structure is only vaguely described as a 'P&L report.'
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 0%, but the description compensates well by explaining all three parameters: entity_name (entity to generate report for) and start_date/end_date (with YYYY-MM-DD format and optionality). This goes beyond the schema, which only provides defaults and no 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 the verb 'Generates' and the specific resource 'Profit & Loss (Income Statement) report in JSON format,' making the tool's purpose unambiguous. It also contrasts with sibling tools like record_cash_sale and create_ledger, which are recording operations, so there is no confusion with other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the sibling context implies it is the reporting tool among recording tools. No when-not conditions or alternative recommendations are provided, so usage guidance is only implied, not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'Records a client invoice' without explaining side effects, reversibility, ledger impacts, or prerequisites. This is a significant gap for a financial transaction tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence followed by a clean bulleted Args list. It front-loads the purpose and provides parameter details without any fluff or redundancy.
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 covers the basic purpose and parameters, but lacks details on return values, ledger interactions, prerequisites, and the meaning of 'entity_name' is ambiguous. For a 5-parameter financial tool with no output schema, it is adequate but has gaps.
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 schema has zero descriptions, so the Args section is the sole source. It adds value with 'Invoice amount (excluding tax)' and 'default: GSTOUT', but other fields like 'Quantity of items invoiced' and 'Entity name to use' are minimal restatements. Some semantics are added, but not comprehensively.
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 states exactly what it does: 'Records a client invoice (credit sale) transaction.' This uses a specific verb and resource, and the '(credit sale)' parenthetical distinguishes it from sibling tools like record_cash_sale and record_supplier_bill.
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 phrase '(credit sale)' clearly indicates this tool is for credit sales to clients, providing context for when to use it. It doesn't explicitly exclude cash sales or mention alternatives, but the sibling names and credit-sale framing make the usage context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the action ('Records a supplier bill') without disclosing side effects, required permissions, reversibility, or what happens after recording (e.g., ledger updates, accounts payable impact). This is sparse for a mutating transaction tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient, with a single-sentence purpose followed by a bullet-style Args list. Every element adds value, and the format is front-loaded and scannable, making it easy for an agent to parse.
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 covers the tool's purpose and all parameters, but lacks behavioral context (side effects, permissions) and any mention of return values. Given no annotations and no output schema, it is minimally complete but leaves gaps for an agent evaluating the tool's full impact.
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 input schema has 0% description coverage, and the description compensates by listing each parameter with meaningful explanations: 'amount' notes 'excluding tax', 'tax_code' shows default 'GSTIN', and 'entity_name' clarifies its role. However, 'entity_name' could be more specific (e.g., whether it refers to supplier or company), so it's not perfect.
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 ('Records a supplier bill') and specifies the nature of the transaction ('credit purchase'). This distinguishes it from sibling tools like record_cash_sale, record_cash_purchase, and record_client_invoice, which handle different transaction types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for supplier bills (credit purchases) but does not explicitly mention alternatives or exclusions. The context is clear enough that an agent can infer when to use this tool versus cash sale/purchase tools, but explicit guidance would improve 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?
With no annotations, the description carries the full burden. It transparently states the output is the same message, implying no side effects or modifications. The behavior is fully disclosed for a simple echo 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 two short sentences, front-loaded with the main verb and object, with the parameter doc as a compact second sentence. Every word is useful.
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 single-parameter utility with no output schema, this description is complete. It fully explains input, behavior, and result, without needing to mention return format since it is self-evident.
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 description explicitly defines the 'message' parameter as 'The message to echo', adding meaning beyond the schema's generic 'Message' title. Although schema coverage is 0%, this single parameter is fully explained.
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 'echoes' with a clear resource 'the input message', clearly distinguishing this tool from the financial sibling tools. Its purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any context or exclusions. The description only states what it does, not when to invoke it.
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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