Finance Intelligence MCP

by Ronit-019

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation4/5
Each tool targets a distinct aspect of expense or budget management. The analytical tools (expense_breakdown, expense_summary, compare_budget_vs_expenses) have some conceptual overlap, but their descriptions clarify the differences (tabular grouping vs. chart-based summary vs. real-time comparison). The CRUD tools are clearly separated by resource (expenses vs. budgets).
Naming Consistency3/5
Most tools follow a verb_noun pattern (list_expenses, add_expense, delete_budgets), but three tools are noun phrases (expense_breakdown, expense_summary, financial_health_score). There is also a minor inconsistency with 'add_expense' vs. 'create_budget', using different verbs for the same create action.
Tool Count5/5
With 12 tools, the server is well-scoped for a financial management domain. Each tool serves a clear purpose, covering CRUD for expenses and budgets plus analytical insights, without excessive fragmentation or unnecessary overlap.
Completeness5/5
The tool surface provides full CRUD for both expenses and budgets, with list operations that support filters to act as read-by-query. Analytical coverage is strong with breakdown, summary, budget comparison, and health score, leaving no obvious dead ends for typical expense-tracking workflows.
Average 3.7/5 across 12 of 12 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 29 commits in the last 12 weeks
- Last stable release on July 4, 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
No annotations are present, so the description carries full burden. It only repeats the tool's name ('Add an expense') without disclosing side effects, validation rules, idempotency, or return behavior. For a write operation, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified to the point of being nearly tautological. Conciseness should serve clarity, and here it sacrifices critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and no annotations, the description fails to provide necessary context. It does not explain what constitutes a valid expense, how categories are structured, or what happens upon success/failure. The tool is too underspecified for reliable use.
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 5 parameters with 0% description coverage, and the description provides no information about parameter meanings, formats, or relationships. The tool name 'expense' plus schema types (e.g., number, string) are not enough for an agent to correctly populate fields like 'subcategory' or 'note'.
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 uses the specific verb 'Add' and identifies the resource 'expense', clearly indicating the primary action. It implicitly distinguishes from sibling tools like 'update_expenses' and 'delete_expenses' through the verb choice, but does not explicitly contrast with them.
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. It does not mention prerequisites, common use cases, or exclude scenarios. With many expense-related sibling tools, some guidance is expected.
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 carries full responsibility for behavioral disclosure. It mentions 'deterministic' (implying reproducible results) but does not state whether the operation is read-only, what data it depends on, or any side effects or prerequisites. This is a notable gap for a financial analysis 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, front-loaded sentence with no filler. It communicates the core function efficiently, which is ideal given the tool's analytical nature.
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?
While the output schema may explain return values, the description omits crucial context such as data sources, prerequisites (e.g., requiring existing expense/budget data), and how the score is derived. For a tool with analytical complexity, this description falls short of being fully contextual.
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 sole parameter reference_month is fully described in the schema (optional, YYYY-MM format, defaults to current month), giving 100% schema coverage. The description adds no param information, so baseline 3 is appropriate.
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 identifies the tool's action ('Calculate') and resource ('a deterministic financial health score and feedback metrics'), distinguishing it from simpler expense/budget list tools. However, it does not explicitly contrast with siblings like compare_budget_vs_expenses or expense_summary, so it earns a 4 rather than a 5.
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 like expense_summary or compare_budget_vs_expenses. It only states what it calculates, leaving the agent to infer usage from the name and siblings.
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 of behavioral disclosure. It only states the function and omits whether the operation is read-only, how aggregation works, any limitations, or output format specifics (though an output schema exists). No side effects or permission requirements are mentioned.
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, clear sentence that concisely conveys the core purpose without unrelated detail. It is front-loaded with the action and resource, making it easy 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 tool has moderate complexity (6 parameters, 2 required) but the schema fully documents parameters and an output schema exists. The description is adequate for understanding the primary function, yet it does not explain the relationship between group_by and breakdown or provide examples. The schema compensates, making this sufficient but not comprehensive.
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 provides descriptions for all 6 parameters (100% coverage), meeting the baseline of 3. The description adds only a vague reference to 'columns or time units' without enriching parameter meaning or clarifying interactions between group_by and breakdown beyond schema details.
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 function using a specific verb ('Summarize and breakdown') and resource ('expenses'), and specifies the grouping dimensions ('by columns or time units') and date range scope. This distinguishes it from siblings like list_expenses (raw listing) and expense_summary (overall summary), which likely lack the breakdown focus.
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 implies the tool is used for generating grouped expense summaries within a date range, but it does not explicitly state when to use it over alternatives or provide exclusions. There is no comparative guidance, leaving usage to inference.
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 provided, the description carries full responsibility for behavioral disclosure. It only mentions 'real-time' and 'AND' combination, but does not state that the operation is read-only, how it handles missing budgets, or any rate limits or permissions. This is insufficient for a tool with zero annotation support.
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-load the purpose and provide the key filter combination rule without any filler. 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?
The tool has a full output schema, so return values are covered. The description adequately covers the purpose and filter behavior, and the parameter schema is complete. However, it lacks usage differentiation from sibling tools, so it's not fully complete. A 4 is appropriate.
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 has 100% description coverage for all 5 parameters, so the baseline is 3. The description adds meaningful semantic value by clarifying that all provided filters are combined using AND, which is not apparent from individual parameter descriptions. This earns a 4.
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 a specific verb ('Get') and a concrete resource ('real-time spending status compared against active budgets on a given reference date'), which distinguishes it from sibling tools like list_expenses or financial_health_score.
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 explicit guidance is provided on when to use this tool versus siblings such as expense_summary or financial_health_score. The only usage hint is the AND filter combination, but there is no mention of scenarios or exclusions.
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 responsibility for behavioral disclosure. It only mentions input modes (single vs. bulk) but does not disclose side effects, permissions required, validation rules, idempotency, or error behavior. For a mutating 'create' 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—two sentences—and front-loads the primary purpose. Every word adds value, and it avoids repeating schema 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?
Given the tool's complexity (8 optional parameters, two distinct usage modes), the description is brief and does not specify which fields are required for single vs. bulk creation, nor does it clarify the structure of the budget dicts in the bulk mode. An output schema exists, so return values are covered, but the description leaves some ambiguity about how to correctly compose a request.
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 the schema already documents all parameters well. The description adds meaningful usage context by explaining that callers can either provide single parameter fields or a list of budget dictionaries via 'budgets', clarifying a non-obvious alternative input mode. This exceeds the baseline for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') and a concrete resource ('budget tracking limits'), clearly distinguishing it from siblings like list_budgets, update_budgets, and delete_budgets. It also clarifies that the tool supports both single and bulk creation via the 'budgets' parameter, reinforcing its purpose.
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 states the tool's capability (creating budgets) but does not explicitly explain when to use it versus alternatives, nor does it mention prerequisites or exclusions. The intended context is implied by the verb 'Create' and the sibling tool names, but no direct guidance is provided.
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 provided, the description carries the full burden of behavioral disclosure. It adds useful context about the AND combination of filters and the mandatory filter/value requirement. However, it does not disclose whether updates are additive or replacing, what happens when no budgets match, or any side effects, which limits transparency for a mutation 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 two sentences long, front-loaded with the action, and every word earns its place. The first sentence states what the tool does; the second adds the necessary constraints without 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?
Given the tool's complexity (12 parameters, no annotations, but an output schema exists), the description covers the essential filter/update semantics but lacks details on edge cases like empty results, partial updates, or interaction between filter fields. It is adequate but leaves room for more operational guidance.
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 provides 100% descriptive coverage for all parameters, so the description does not need to compensate significantly. It introduces the concepts of 'target filters' and 'specified values' but does not explicitly map which parameters belong to each group; the schema already communicates this via the 'filter_' prefix and 'New' 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 action ('Update budgets') and the mechanism ('matching the target filters with the specified values'). This distinguishes it from sibling tools like create_budget or delete_budgets, and the phrasing 'target filters' vs 'specified values' conveys the core purpose effectively.
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 provides usage prerequisites ('At least one target filter and one update value must be provided') and explains how filters are combined ('All provided filters are combined using AND'). However, it does not explicitly name alternative tools or state when to prefer this tool over similar update operations, leaving some selection ambiguity.
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 provided, the description carries the full burden for behavioral disclosure. It does add a useful behavioral trait by explaining that filters are combined with AND, which is non-obvious from the schema alone. However, it does not disclose other potentially relevant behaviors such as pagination, sorting, default limit, or the handling of no filters (though 'all' is implied). It is adequate but not rich.
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 consists of two short, front-loaded sentences. The first states the core action and the second adds a critical behavioral detail. No filler, repetition, or unnecessary information. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (4 optional parameters, all described in schema, output schema present), the description is mostly complete. It explains the core filtering behavior and the AND conjunction. Minor gaps like sorting or pagination behavior are not mentioned, but for a simple listing tool with a documented output schema, this is acceptable.
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 descriptions cover all 4 parameters with 100% coverage, providing the baseline of 3. The description adds meaningful semantic value beyond the schema by clarifying that all provided filters are combined using AND, which directly impacts how an agent should construct multi-parameter calls. This elevates the score above baseline.
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 action ('List all budgets') with the resource and optional filter scope. It explicitly distinguishes from sibling tools like list_expenses by naming 'budgets' as the target resource, and the mention of 'optional filters' adds scope beyond a generic listing.
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 does not provide any guidance on when to use this tool versus alternatives like list_expenses or compare_budget_vs_expenses. There is no mention of prerequisites, exclusions, or scenarios where another tool would be more appropriate. The only usage hint is the implied purpose of listing budgets.
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 provided, the description carries the full burden of behavioral disclosure. It does disclose the AND logic and the requirement for both a filter and a value, which is useful. However, it omits important behavioral details such as what happens if no expenses match, whether omitted values remain unchanged, and any idempotency or authorization concerns. This is an adequate but not rich behavioral description.
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 sentences, front-loaded with the main action, and every clause earns its place. It communicates the core action, a mandatory constraint, and the filter combination logic without waste. Excellent brevity.
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?
This is a 10-parameter mutation tool with no annotations, so the description needs to cover the essential invocation rules. It does state the filter+value requirement and AND semantics, which are critical. However, it does not clarify the role of expense_ids, nor does it explain behavior when multiple rows match, no match, or whether updates are partial. Given the tool's complexity and lack of annotation support, the description is somewhat incomplete.
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 100% description coverage, so the baseline is 3. The description adds some semantic grouping by distinguishing 'target filters' from 'specified values', but it does not explicitly map which parameters fall into each group. This leaves ambiguity, especially for expense_ids, which could be interpreted as either a filter or an update value. The description therefore provides only marginal added value over 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 updates expenses matching target filters with specified values, which is a specific verb+resource combination. It distinguishes itself from sibling tools like add_expense, delete_expenses, and list_expenses. The critical constraint (at least one filter and one value) adds important purpose clarity.
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 context: updating existing expenses, with a mandatory rule that at least one target filter and one update value must be provided. It also explains filters are AND-combined, which guides selection of parameters. However, it does not explicitly mention alternatives or when not to use this tool, so it misses the highest bar.
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 carries the full burden of behavioral disclosure. It does add meaningful context by explaining the safety guardrail (at least one filter required) and the AND-combination behavior, which are not visible in the schema. However, it does not mention irreversibility, confirmation prompts, or what happens if the filter condition is invalid, which are relevant for a destructive 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 extremely concise: two sentences, with the main action in the first sentence and the key constraints in the second. No filler or redundant wording. It is front-loaded and every sentence 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?
Given the moderate complexity (5 optional params with filter interactions) and the presence of an output schema, the description covers the essential invocation logic: what the tool does, how filters combine, and the safety constraint. It does not explain the exact return format, but that is expected to be in the output schema. A minor gap is that it does not state what error occurs if no filters are provided, though the requirement is explicit.
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 already provides 100% coverage of parameter descriptions, but the tool description adds critical cross-parameter semantics: that all provided filters are combined using AND and that at least one is required. This goes beyond the per-field schema descriptions and clarifies how parameters interact, elevating the semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Delete expenses matching the provided filters.' It uses a specific verb ('delete') and resource ('expenses'), and distinguishes itself from sibling tools like list_expenses and update_expenses by focusing on deletion. The AND-combination detail further clarifies its scope.
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 provides an important usage constraint: 'At least one filter must be provided to prevent accidental deletion of all records.' This implies the tool is for targeted deletions, and implicitly warns against calling it without filters. However, it does not explicitly contrast with alternatives or state when not to use it, so usage context is mostly implied.
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?
Since no annotations are provided, the description must disclose behavioral traits itself. It only mentions chart generation but does not state whether the operation is read-only, whether it has side effects (e.g., saving files), or how the chart is returned. It also omits fallback behavior when no grouping is given, leaving important operational details undisclosed.
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: two sentences, with the core purpose in the first and a practical recommendation in the second. It contains no fluff or repetition, making it maximally efficient and easily scannable.
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 (which likely covers return values) and full schema coverage for parameters, the description is sufficiently comprehensive for the tool's moderate complexity. It lacks detail on chart specifics or edge cases, but the essential purpose and key usage note are present, so it is not incomplete.
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 already documents all six parameters (100% coverage), so the baseline is 3. The description adds non-redundant value by framing 'period' and 'group_by' as grouping dimensions and recommending that at least one be used. This helps the agent understand the intended relationship and prioritization among the optional 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 specifies a clear verb ('Generate'), a resource ('expense summary'), and distinguishing attributes ('analytical', 'rich Matplotlib chart'). This positions it as a distinct analytical tool compared to siblings like list_expenses (which lists) and expense_breakdown (which breaks down), leaving no ambiguity about its core function.
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 recommendation to use at least one grouping dimension ('period' or 'group_by') provides clear, actionable guidance on how to invoke the tool effectively. However, it does not explicitly contrast the tool with alternatives like expense_breakdown or list_expenses, so an agent might not know when this summary/chart tool is preferable over those siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description conveys the destructive nature implicitly through 'delete' but doesn't disclose permanence, permissions, or the interaction between budget_ids and other filters. It does add the AND-combination rule, which is useful but basic.
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 short sentences deliver the core action and necessary constraints, with no redundant words or repetition of schema details.
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 tool has 7 parameters but full schema coverage and an output schema reduce the need for description. The description provides essential guardrails for safe deletion, though it could mention irreversibility or error behavior for missing filters.
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 all parameters are already described. The description adds meaningful cross-parameter behavior: 'at least one filter' and 'AND' combination, which go beyond the individual 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 uses a specific verb and resource, 'Delete budgets', and clarifies the filter-based targeting. It clearly distinguishes the tool from siblings like delete_expenses and update_budgets.
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 states when to use the tool by requiring at least one filter and explains that all filters are combined with AND. It doesn't explicitly mention alternatives but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It goes beyond basic 'list' semantics by revealing two important behaviors: truncation to 50 inline results and export of the full dataset to a CSV spreadsheet. It also clarifies that the date range is inclusive. However, it does not specify the ordering of results before truncation or how the CSV export is delivered, which are minor gaps given the absence of an output schema.
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 efficient: two sentences, the first stating the core purpose and the second disclosing critical behavior. It is front-loaded with the action and resource, and every sentence adds value. There is no redundant or filler content.
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 relatively simple listing tool with two date parameters and no output schema, the description is fairly complete. It covers the main functionality, the date-range inclusivity, the truncation rule, and the CSV export fallback. The main missing details are ordering and CSV delivery mechanism, but these are not major for a basic retrieval tool. The context is sufficient for an AI agent to invoke it correctly in most use cases.
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 only two string parameters (start_date and end_date) with 0% description coverage, so the description must compensate. It adds the meaning that these define a date range and that the range is inclusive, which is useful. However, it does not specify the expected date format (e.g., YYYY-MM-DD) or any validation constraints like start date must be before end date. This is partial compensation but leaves gaps for an agent to infer format correctly.
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 all expenses from the database within a date range. It uses specific verbs and resource references ('List all expenses'), and the sibling tools make the distinction clear (e.g., add_expense, delete_expenses, compare_budget_vs_expenses). The scope is well-defined, and there is no ambiguity about what the tool does.
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 when to use the tool: when a user needs to retrieve expenses over a specific period. It clearly distinguishes from sibling tools like list_budgets or expense_summary by focusing on raw expense records. However, it does not explicitly state when not to use it or mention alternative tools for filtered or summarized views, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![Finance-Intelligence-MCP MCP server](https://glama.ai/mcp/servers/Ronit-019/Finance-Intelligence-MCP/badges/card.svg)](https://glama.ai/mcp/servers/Ronit-019/Finance-Intelligence-MCP)

Score Badge

Copy to your README.md:

[![Finance-Intelligence-MCP MCP server](https://glama.ai/mcp/servers/Ronit-019/Finance-Intelligence-MCP/badges/score.svg)](https://glama.ai/mcp/servers/Ronit-019/Finance-Intelligence-MCP)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Ronit-019/Finance-Intelligence-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server