Luni MCP Server

Server Quality Checklist

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Latest release: v0.4.0
Disambiguation5/5
Each tool has a distinct purpose clearly separated by personal vs. business context. Overlapping concepts like cash flow vs. P&L are explicitly differentiated in descriptions, and personal tools are marked as separate from business entity tools.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, with either 'get_' or 'list_' prefixes. No mixing of conventions or irregular patterns.
Tool Count5/5
With 8 tools, the server covers personal and business financial querying needs without being excessive. Each tool serves a specific, necessary function in the domain.
Completeness5/5
The tool set covers essential read operations for both personal (budget, transactions, split debts) and business (cash flow, P&L, partner distribution, recurring items) finance. No obvious gaps for querying, especially with prerequisite tool list_entities.
Average 4.2/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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?
Annotations already indicate readOnlyHint=true. Description adds that it shows revenue, expenses, etc., but no additional behavioral details beyond what annotations provide. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, front-loaded with purpose and usage. Every word earns its place.
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?
For a tool with no output schema, description provides enough context on what is returned (revenue, expenses, etc.). Could be more detailed on format but adequate given complexity.
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?
Input schema covers all 5 parameters with descriptions. Description does not add value beyond schema; schema coverage is 100% so baseline 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?
Description clearly states the tool returns a P&L statement for a business entity with specific line items, and it distinguishes from siblings like get_cash_flow and get_budget_status.
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?
Explicitly states when to use (user asks about profitability, revenue, etc.) and prerequisite call to list_entities. Missing explicit when-not-to-use but clear 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?
Annotations already declare readOnlyHint=true and destructiveHint=false, making safety clear. The description adds minimal behavioral context beyond listing examples; it does not mention response format, pagination, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences plus a practical usage hint. No redundancy; every sentence adds value.
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?
For a simple list tool with well-documented parameters and no output schema, the description covers purpose, usage context, and prerequisite. Missing return format details, but overall 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 is 100%, so parameters are fully documented in the schema. The description adds no new semantic meaning beyond what the schema provides, meeting the baseline of 3.
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 the resource 'recurring inflows and outflows' with examples (subscriptions, retainers, etc.), distinguishing it from siblings like list_transactions or get_cash_flow.
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?
Explicitly says when to use (fixed costs, recurring revenue, SaaS spend) and provides a prerequisite (call list_entities). Lacks explicit when-not-to-use or alternatives, but the guidance is clear and actionable.
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?
Annotations already indicate read-only and non-destructive. Description adds output context (who owes whom) but no additional behavioral traits beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with a list of examples. Front-loaded with core functionality, no unnecessary 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?
Simple tool with one optional parameter and no output schema; description sufficiently explains purpose and output (who owes whom). Complete for the tool's complexity.
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% with a well-described optional parameter (friend_name_contains). Description does not add extra 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 the tool lists unsettled split transactions, with examples of use cases. This differentiates it from sibling tools like get_cash_flow or get_pnl.
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 use cases like 'who owes me' and 'do I owe anyone', guiding when to use. Lacks exclusion criteria for when not to use, but use cases are specific enough.
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?
Beyond the readOnlyHint annotation, the description reveals role-based visibility: partners see only their share, owners see the full split. This is important behavioral context that annotations alone do not provide.
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 very concise—four short sentences—with the main purpose stated first. Every sentence adds value: purpose, behavior, example queries, and prerequisite call to action.
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 no output schema and simple annotations, the description covers purpose, when to use, behavioral nuance, and a prerequisite. It does not describe the output structure, but the term 'distribution summary' implies a breakdown, which is 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?
The schema already provides descriptions for all parameters with 100% coverage. The description only reiterates that entity_id should come from list_entities, which is already in the schema description. No additional parameter meaning is added.
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 a profit distribution summary for a business entity, specifying how net profit is split between partners. This distinguishes it from sibling tools like get_pnl or get_cash_flow which deal with different financial aspects.
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 example user queries that trigger this tool ('how much do I take home', etc.) and advises to call list_entities first for the entity_id. It does not explicitly exclude when not to use or compare with alternatives, but the examples give clear usage context.
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 declare readOnlyHint=true and destructiveHint=false. Description adds context about the scope of entities listed (user's accessible) and the need for entity_id in sibling tools. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines the action, second provides usage guidance and dependencies. Efficiently packed with no unnecessary 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?
Complete for a simple list tool: describes purpose, usage trigger, and output importance. Annotations cover behavioral aspects. No missing info.
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% with a well-documented enum. Description does not repeat parameter details, which is appropriate. No additional semantics needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists business entities and personal spaces. It specifies usage context ('Call this first when the user asks about a company, partnership, or business account') and distinguishes from siblings by noting the returned entity_id is required by multiple 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to call this first when the user asks about a company/partnership/business account. Implicitly provides when-not but no explicit exclusions. The mention of downstream tool dependency gives strong guidance on workflow.
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 declare readOnlyHint=true and destructiveHint=false, so the description adds the specific behavioral context of comparing budget to actual spend. This is useful but does not detail output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, followed by usage examples and alternative reference. 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?
The description explains the tool's output concept (budget vs actual) and usage, but doesn't explicitly state the return structure (e.g., per-category breakdown). The example queries imply category-level granularity, so it's mostly complete for a simple tool without output schema.
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 single parameter 'month' is fully described in the schema with format and default. The description only reiterates the month can be specified, adding no new semantic information 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?
Clearly states the tool shows 'personal budget vs actual spend' for a month. Distinguishes from sibling get_pnl by explicitly noting business-entity P&L should use a different tool.
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?
Provides explicit user query examples ('how am I doing', 'am I over budget') and directs to alternative get_pnl for business P&L. Clearly defines when to use and when not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds value by detailing what the tool returns (inflows, outflows, net, breakdowns) and the grouping behavior, going beyond the annotations.
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, consisting of two focused sentences with no unnecessary words. Every sentence serves a purpose: explaining output, providing usage context, and giving a prerequisite.
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 four parameters and no output schema, the description covers the tool's purpose, usage context, and key output characteristics. While it does not detail the exact response structure, it sufficiently informs the agent about what to expect.
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?
With 100% schema coverage, the baseline is 3. The description adds context by relating the group_by parameter to the output (e.g., 'by category or by month') and reiterating the need to call list_entities for entity_id, which enhances understanding 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 identifies the tool as returning a cash flow summary for a business entity, specifying inflows, outflows, net, and breakdowns by category or month. It distinguishes itself from sibling tools like get_pnl or get_budget_status by focusing on cash flow rather than profit/loss or budget.
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 states when to use the tool (e.g., questions about revenue vs expenses, monthly cash position) and provides a prerequisite (call list_entities for entity_id). However, it does not mention situations where an alternative sibling tool might be more appropriate.
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 declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds valuable context: 'Returns transactions across all connected accounts (Plaid + Wise) for the authenticated Luni user.' It also specifies personal vs. business scope. However, it does not mention return format or pagination, which would be helpful since no output schema exists.
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 at three sentences, each adding distinct value: purpose, usage context, and exclusion/alternatives. No wasted words, front-loaded with the key action.
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 complexity (7 optional parameters, no output schema), the description covers purpose, scope, and alternatives. It lacks mention of return format or pagination, but the schema documents parameters well. For a tool with read-only annotations and clear sibling differentiation, it is largely complete.
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% with each parameter having a clear description. The tool description does not add further meaning to the parameters beyond the schema. Baseline score of 3 is appropriate as the schema does the heavy lifting.
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 'List the user's personal Luni transactions' with a clear verb and resource. It also distinguishes from sibling tools by saying 'For business-entity spending, call get_pnl or get_cash_flow instead.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this whenever the user asks about their own spending, recent purchases, a specific merchant, or a category total.' It also gives clear when-not-to-use and alternatives for business spending.
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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