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samu187

expenses-tracker-mcp

by samu187

Expenses Tracker

A local-first expense tracking app built with FastAPI, SQLite, React, and Vite.

The backend stores transactions in a local SQLite database, serves the API under /api, and serves the built React frontend from the FastAPI app. The project also includes an MCP server for querying and classifying transactions from compatible coding agents.

Features

  • Import bank statement CSV files

  • Add, edit, delete, filter, and classify transactions

  • Maintain accounts and account groups

  • View monthly overview, category totals, and daily reports

  • Run a local MCP server for agents to automatically classify your transactions

Related MCP server: Expense Tracker MCP Server

Project structure

src/expenses_tracker/
  cli.py                  Command-line entry point
  web.py                  FastAPI app and web-server runner
  database.py             SQLite setup and seed accounts
  transactions.py         Transaction data operations
  import_statement.py     CSV statement import logic
  api/routes.py           API routes
  mcp/server.py           MCP server for expense tools
  static/                 Built frontend served by FastAPI

frontend/
  index.html              Vite entry HTML
  src/                    React source
  vite.config.js          Builds into src/expenses_tracker/static

Requirements

  • Python 3.12+

  • uv

  • Node.js and npm

Setup

Install Python dependencies:

uv sync

Install frontend dependencies:

cd frontend
npm install

Build the frontend

The FastAPI app serves the compiled frontend from src/expenses_tracker/static.

cd frontend
npm run build

Run the Web App

uv run expenses web

The app starts on http://127.0.0.1:8125 and opens the default browser automatically.

Bank statement imports

The transaction screen imports a CSV file selected through the browser. The API requires the selected file's name and content in the request body.

Expected CSV columns:

  • Transaction Date in DD/MM/YYYY format

  • Transaction Description

  • Debit Amount

  • Credit Amount

Debit amounts are stored as negative pence values. Credit amounts are stored as positive pence values. Imported transactions are assigned to the Pending account by default.

API overview

  • GET /api/health

  • GET /api/account-groups

  • GET /api/accounts

  • POST /api/accounts

  • GET /api/transactions

  • POST /api/transactions

  • PATCH /api/transactions/{transaction_id}

  • DELETE /api/transactions/{transaction_id}

  • POST /api/import-bank-statement

MCP server

Run the MCP server with:

uv run expenses mcp

Available tools include:

  • guarded read-only SQL queries

  • transaction listing with filters

  • account listing

  • pending transaction grouping

  • classification summaries

  • account assignment for selected transactions or filtered batches

Use dry-run mode before bulk classification changes.

Development notes

  • Frontend source lives in frontend/src.

  • Frontend build output is committed under src/expenses_tracker/static so the FastAPI app can serve the UI directly.

  • Local runtime data is stored outside the repository in the operating system's user-data directory.

Available Tools

8 tools
bulk_update_by_filterC

Assign all transactions matching a filter to an account, or preview with dry_run.

ParametersJSON Schema
NameRequiredDescriptionDefault
monthNo
commentNo
dry_runYes
account_idYes
updated_byYes
account_groupNo
amount_max_penceNo
amount_min_penceNo
counterparty_exactNo
counterparty_containsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description bears full responsibility for behavioral disclosure. It only mentions the dry_run preview; it does not state potential side effects, reversibility, permission needs, or that this is a mutating bulk operation. This is a significant gap for a tool that assigns transactions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence with no wasted words. It front-loads the action and resource. However, it sacrifices necessary detail for brevity, so it is not a 5.

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?

For a complex tool with 10 parameters, no annotations, and only a generic filter mention, the description is critically incomplete. It omits required parameter semantics, filter options, and behavior of dry_run results, even if an output schema exists.

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?

Schema coverage is 0%, and the description does not name or explain any of the 10 parameters. It only generically says 'a filter', leaving account_id, dry_run, updated_by, and all filter fields semantically undefined.

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 assigns all transactions matching a filter to an account, with an optional dry_run preview. This distinguishes it from sibling tools like update_transactions_account, which likely handles single transactions.

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 phrase 'all transactions matching a filter' implies batch use, but no explicit comparison or exclusion of alternatives (e.g., update_transactions_account) is provided. The dry_run mention hints at safe testing, but without stated when-to-use/when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

create_accountB

Create an account in an existing account group.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYes
account_group_idYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.3/5.0
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 states the action (create) but does not disclose any side effects, auth requirements, or constraints beyond the implicit existence of the group. This is a minimal level of disclosure 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that efficiently conveys the core purpose. It is front-loaded with the primary action and avoids filler, though it could have included slightly more contextual detail without becoming verbose.

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 creation tool with two parameters, the description provides the essential purpose. The presence of an output schema reduces the need to explain return values, but the description lacks usage guidance and behavioral context, leaving it at a minimally sufficient level for a tool of this simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, and the tool description adds no parameter-specific meaning. While the param names (name, account_group_id) are somewhat self-explanatory, the description does not clarify formats, uniqueness, or any other nuances, so it fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Create') and resource ('account'), clearly indicating the operation. It also specifies the context ('in an existing account group'), which distinguishes it from any hypothetical group-creation tool and from the sibling read 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 phrase 'in an existing account group' implicitly tells the agent that the account group must already exist, implying a prerequisite. However, it does not explicitly state when to use this tool over alternatives or provide exclusions, limiting guidance to an implied usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_classification_summaryB

Summarize transactions grouped by counterparty, account, or account group.

ParametersJSON Schema
NameRequiredDescriptionDefault
monthNo
group_byYes
account_groupNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3/5.0
Behavior2/5

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 only states the basic summary action but does not disclose what metrics are computed (e.g., counts, totals), how the month and account_group filters behave, or the return format. This leaves significant behavioral ambiguity for a summary 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 fluff. Every word contributes meaning, and the sentence structure is clear and direct.

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?

Given three parameters, no annotations, and no explanation of the summary output or filters, the description is too minimal for reliable use. Although an output schema exists, the description still needs to convey how grouping and filters operate; it does not, leaving the tool incomplete for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the group_by enum values but fails to mention the month and account_group parameters or their filtering semantics. Only partial parameter understanding is achieved, lacking guidance on optional filters.

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 action (summarize) and resource (transactions), and explicitly lists the grouping options (counterparty, account, account_group), which brings it close to a 5. However, it does not explicitly distinguish this from sibling tools like list_transactions, so it stops short of full differentiation.

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 for summarizing transactions when grouping is needed, but it does not provide explicit guidance on when to use this tool versus siblings like list_transactions or update_transactions_account. No exclusions or alternative references are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_accountsB

List accounts, optionally filtered by account group name.

ParametersJSON Schema
NameRequiredDescriptionDefault
account_groupNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must disclose behavioral traits, but it only states 'List accounts' without mentioning that it is read-only, any error conditions, or return format. The implicit read-only nature is not explicit, leaving the agent without critical safety context.

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, concise sentence that front-loads the primary action and immediately mentions the optional filter. Every word is necessary and there is no 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?

For a simple tool with one optional parameter and an output schema, the description is minimally adequate. However, it lacks usage guidance relative to sibling tools and does not compensate for the absence of annotations, making it incomplete for an agent to confidently invoke.

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 no description for the account_group parameter (0% coverage), so the description's mention of 'optionally filtered by account group name' adds basic meaning. However, it does not clarify matching behavior (exact vs partial) or what passing null means beyond the word 'optionally.'

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: 'List accounts' with an optional filter by 'account group name.' It is a specific verb+resource construction that distinguishes from sibling tools like list_transactions or list_pending_groups, which target different entities.

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 such as run_readonly_sql or list_pending_groups. It only mentions an optional filter, giving no context on selection criteria or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_pending_groupsC

List pending transactions grouped by counterparty.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
monthNo
account_groupNopending

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must disclose behavioral traits, but it only mentions 'pending' and 'grouped by counterparty'. It does not state whether the operation is read-only, how grouping is defined, what happens with the month parameter, or how pagination works via limit. The minimal description leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no unnecessary words. It efficiently conveys the core purpose. While it could be expanded with more detail without becoming verbose, the current structure is concise.

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?

The tool has three optional parameters, no parameter descriptions, no annotations, and relies on an output schema. The description fails to explain parameter semantics, the meaning of 'pending', grouping behavior, or defaults. This is under-specified for a tool with multiple configuration options, even though the output schema covers return values.

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?

Schema description coverage is 0%, so the description must compensate. However, the description does not mention any of the three parameters (limit, month, account_group). It provides no meaning for these parameters beyond what the schema's default values imply. The agent receives no explanation of how 'month' filters or how 'account_group' interacts with 'pending'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'List pending transactions grouped by counterparty.' It includes a specific verb ('List'), a resource ('pending transactions'), and a grouping dimension. However, it does not explicitly distinguish itself from sibling tools like list_transactions or run_readonly_sql, which could also list transactions.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or context where list_pending_groups is preferred over list_transactions or run_readonly_sql. It merely restates the function without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_transactionsA

List transactions using optional month, account, counterparty, and amount filters.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
monthNo
offsetNo
account_idNo
account_groupNo
amount_max_penceNo
amount_min_penceNo
counterparty_exactNo
counterparty_containsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden of behavioral disclosure. It states the action is to list transactions, which implies a read-only operation, but does not explain pagination, ordering, or how filters are combined. However, it is not misleading, so a middle score is appropriate.

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 wasted words. It efficiently states the tool's purpose and indicates optionality of filters.

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 having 9 parameters and no annotations, the description is extremely sparse. It omits key context like pagination parameters (limit/offset), filter interaction semantics, and any mention of the output schema or default behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions high-level filter categories but does not name any of the 9 parameters, clarify unit semantics (e.g., pence), or distinguish between exact and contains matching for counterparty.

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 transactions with optional filters for month, account, counterparty, and amount. This specific verb and resource distinguish it from sibling tools like list_accounts or run_readonly_sql.

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 usage for listing transactions but gives no explicit guidance on when to choose this tool versus alternatives. It does not mention exclusions or when another tool would be more appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

run_readonly_sqlC

Run a guarded read-only SQL query and return columns plus rows.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
paramsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.7/5.0
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 mentions 'guarded read-only', which suggests safety, but 'guarded' is vague and does not disclose what exactly is guarded (e.g., only SELECT allowed, blocking DDL/DML). No mention of authentication, rate limits, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence that states the action and return value. It is concise and front-loaded, with no waste. However, it is under-specified for a SQL tool, so while concise, it sacrifices necessary detail.

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?

With no annotations and a bare-bones description, the agent receives insufficient context for a tool with 3 parameters and safety implications. The output schema exists but is not described. The description is too sparse to fully guide correct invocation, especially regarding query safety and parameter handling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no parameter information. The schema lists 'query', 'limit', and 'params', but the description does not clarify 'params' (e.g., positional vs named) or how the limit works. It relies entirely on the schema, which has minimal descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Run') and resource ('read-only SQL query'), and mentions that it returns columns and rows. It distinguishes itself from the specialized sibling tools by being a generic SQL interface. However, it does not explicitly differentiate from tools like list_transactions, though the SQL nature is clear.

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?

There is no guidance on when to use this tool versus alternatives. The phrase 'guarded read-only' implies a safety constraint but not when to prefer this over specialized list tools. It lacks any exclusions or explicit alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

update_transactions_accountC

Assign specific transactions to an account.

ParametersJSON Schema
NameRequiredDescriptionDefault
commentNo
account_idYes
updated_byYes
transaction_idsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.3/5.0
Behavior1/5

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 only restates the action without explaining side effects, overwrite semantics, reversibility, or permission requirements, offering no value beyond the name itself.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler words. It is concise and efficiently phrased, though it sacrifices substance for brevity.

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?

The tool has 4 parameters, no annotations, and an output schema, yet the description provides almost no operational context. It fails to explain the update semantics, prerequisites, or any edge cases, making it inadequate for reliable invocation.

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?

Schema coverage is 0%, and the description does not explain any parameters. It mentions 'transactions' and 'account' but ignores transaction_ids, account_id, updated_by, and comment, leaving the agent without critical semantic information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Assign') and the resource ('specific transactions to an account'). It is specific enough to understand the core function, though it does not explicitly differentiate from sibling tools like bulk_update_by_filter.

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, such as bulk_update_by_filter. The description implies targeted assignment but does not state exclusions or preferred scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 8 tool updatesv0.1.0
    • First observedbulk_update_by_filter
    • First observedcreate_account
    • First observedget_classification_summary
    • First observedlist_accounts
    • First observedlist_pending_groups
    • First observedlist_transactions
    • First observedrun_readonly_sql
    • First observedupdate_transactions_account

TDQS

B3.1/5.0

Scored across 8 tools

Disambiguation4/5

Tools are mostly distinct: raw SQL, list operations, update operations, and create account each target a unique action. However, list_pending_groups and get_classification_summary both group transactions, and update_transactions_account vs bulk_update_by_filter could be confused, though descriptions clarify the difference.

Naming Consistency4/5

The majority follow a clear verb_noun pattern (list_, create_, update_, get_). Minor deviations like bulk_update_by_filter and run_readonly_sql are still readable and consistent in style, so the overall pattern is predictable.

Tool Count5/5

8 tools is well-scoped for an expense tracking server. Each tool serves a clear purpose in querying, updating, or creating accounts, with no redundant or missing trivialities.

Completeness3/5

The surface covers listing, classification, account creation, and transaction updates, but lacks a create_transaction tool, which is a core operation for an expense tracker. Also missing account update/delete, leaving notable gaps for full lifecycle management.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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