Personal Expense Tracker MCP は、個人の支出を追跡するためのシンプルなローカル MCP サーバーです。
支出データはローカル CSV ファイルに保存されます。
このサーバーは、MCP クライアントに 5 つの主要なツールを提供します。
新しい支出を追加する
保存済みの支出を一覧表示する
支出のサマリーを作成する
既存の支出を更新する
既存の支出を削除する
このプロジェクトは、シンプルでローカルで簡単に実行できるように作られています。
銀行口座や外部 API は必要ありません。
Related MCP server: Expense Tracker MCP
開始する前に、以下のものがインストールされていることを確認してください。
Node.js バージョン 20 以降
npm
Git
Node.js を確認する
node --versionnpm を確認する
npm --versionGit を確認する
git --versiongit clone https://github.com/MohammadYousef-001/Personal-Expenses-Tracker.gitcd Personal-Expenses-Trackernpm installnpm が必要なパッケージのインストールを完了するまで待ちます。
支出はローカルの次の場所に保存されます。
data/expenses.csvCSV ファイルは次の列を使用します。
id,amount,category,date,description列名は変更しないでください。
サーバーを起動するには、以下を実行します。
npm run devこのサーバーは、MCP 通信に標準入力と標準出力を使用します。
ローカルサーバーであるため、Web ポートは必要ありません。
MCP Inspector は、ツールを手動でテストするための最も簡単な方法です。
以下を実行します。
npm run inspectMCP Inspector が表示されたブラウザウィンドウが開きます。
自動的に開かない場合は、ターミナルに表示された URL を使用します。
Inspector では次の手順を実行します。
サーバーに接続する
Tools セクションを開く
ツールを選択する
入力値を入力する
Execute Tool をクリックする
結果を確認する
Tool | 説明 | 主な入力 |
| 新しい支出を CSV ファイルに追加する | amount category date description |
| 保存済みの支出を一覧表示し、絞り込むことができる | month category |
| 月ごとの支出合計を計算する | month |
| 既存の支出を 1 件更新する | id と少なくとも 1 つの支出フィールド |
| 既存の支出を 1 件削除する | id |
新しい支出を保存するには、add_expense を使用します。
amount
支出した金額です。
正の数である必要があります。
category
支出のカテゴリです。
例:
groceries
transport
bills
shoppingカテゴリ名を一定に保つため、カテゴリは小文字で保存されます。
date
支出の日付です。
次の形式を使用する必要があります。
YYYY-MM-DD例:
2026-08-12日付は実際の暦日でもある必要があります。
これは無効です。
2026-99-99description
支出に関する任意の短い情報です。
{
"amount": 25,
"category": "groceries",
"date": "2026-08-12",
"description": "milk and bread"
}成功したリクエストは、支出を次の場所に追加します。
data/expenses.csv保存済みの支出を表示するには、list_expenses を使用します。
フィルタなし:
{}カテゴリで絞り込む:
{
"category": "groceries"
}月で絞り込む:
{
"month": "2026-08"
}両方のフィルタを使用する:
{
"month": "2026-08",
"category": "groceries"
}月は次の形式を使用する必要があります。
YYYY-MM月は 01 から 12 の間である必要があります。
2026-99支出のサマリーを確認するには、get_spending_summary を使用します。
例:
{
"month": "2026-08"
}結果には次のものが含まれます。
選択した月
支出した合計金額
支出の件数
各カテゴリの支出合計
結果の例:
month: 2026-08
total amount: 150
expense count: 4
category totals:
groceries: 80
transport: 30
bills: 40実際の値は data/expenses.csv 内のデータによって異なります。
I spent 25 on groceries today次を使用できます。
add_expenseshow my grocery expenses for this month次を使用できます。
list_expenseshow much did I spend this month次を使用できます。
get_spending_summaryこのプロジェクトは、ツール入力を使用前に検証します。
無効な入力の例:
負の金額
ゼロの金額
日付形式の誤り
存在しない日付
無効な月
長すぎるカテゴリ
長すぎる説明
無効な入力は保存される前に拒否されます。
以下を実行します。
npm run check:schema成功すると、次のように表示されます。
All expense schemas are valid.パッケージまたはモジュールが見つからないというエラーが表示された場合は、以下を実行します。
npm installその後、もう一度試してください。
npm run devパッケージがインストールされていることを確認してください。
npm installその後、以下を実行します。
npm run inspect古い Inspector プロセスがまだ実行されている場合は、次のキーを押してください。
Ctrl + Cその後、Inspector を再度起動します。
以下を実行します。
npm run check:schemaすべて正しければ、次の結果が表示されます。
All expense schemas are valid.エラーがある場合は、ターミナルに表示されたファイル名と行番号を確認してください。
エラーを修正してから、Inspector を再度起動します。
有効な日付は次の形式を使用する必要があります。
YYYY-MM-DD有効な例:
2026-08-12無効な例:
2026-99-99次を確認してください。
data/expenses.csvCSV ヘッダーの下に支出の行が含まれていることを確認してください。
ファイルにヘッダーしかない場合は、空の結果が正常です。
重要なプロジェクトファイル:
Personal-Expenses-Tracker/
│
├── data/
│ └── expenses.csv
│
├── docs/
│ ├── design.md
│ └── threat-model.md
│
├── examples/
│
├── src/
│ ├── index.ts
│ ├── schemas/
│ ├── tools/
│ └── lib/
│
├── SECURITY.md
├── package.json
└── README.mdツールの入力は、信頼できない入力として扱われます。
このプロジェクトは、重要な操作の前に入力を検証します。
支出ファイルのパスはアプリケーションが管理します。
MCP クライアントに返されるエラーは短く保たれます。
詳細なエラーはデバッグ用にローカルのターミナルに残ります。
支出ツールは外部ネットワークリクエストを必要としません。
詳細なセキュリティ情報は次の場所にあります。
SECURITY.mdこのプロジェクトは、小規模なローカル個人支出トラッカーです。
次のものは含まれません。
銀行口座との接続
銀行情報の自動取り込み
ユーザーログイン
クラウドデータベース
本格的なグラフィカルアプリケーション
財務予測
主な目的は、ローカルの支出追跡に利用できるシンプルな MCP ツールを提供することです。
このプロジェクトは MIT ライセンスを使用しています。
LICENSE を参照してください。
add a new expense
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | The expense date in YYYY-MM-DD format | |
| amount | Yes | The expense amount, up to 1000000 | |
| category | Yes | The normalized expense category | |
| description | No | A short optional description of the expense |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, so the description does not need to restate that this is a write operation. However, it adds no behavioral context beyond what the name implies—it simply restates 'add a new expense', which is effectively a tautology. There is no mention of side effects, idempotency, validation rules, or what happens on conflict, making it entirely uninformative for behavioral expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (five words), which could be seen as concise, but it is under-specified rather than efficiently structured. It lacks any front-loaded information beyond a bare verb phrase. There is no hierarchy of information; it is merely a label, failing to earn its place by providing any useful detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With four parameters, three of which are required, and no output schema, the description is completely inadequate. It does not mention required fields, expected input format (though schema covers this), possible side effects, or return behavior. An agent has no way to anticipate the tool's behavior or success criteria beyond the raw schema, making the description insufficient for correct invocation in a meaningful context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage of all four parameters, including descriptions for amount, category, date, and optional description. The description adds no parameter-specific meaning, so the baseline score of 3 applies. While the description doesn't harm parameter understanding, it also doesn't supplement the schema or clarify relationships between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'add a new expense' conveys a clear verb (add) and resource (expense). It is distinct from sibling tools like update_expense and delete_expense simply by the verb 'add', so an agent can infer its core purpose. However, it does not explicitly distinguish itself from potential overlap or specify any scope (e.g., personal vs. shared), 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or when 'add' is preferred over 'update' or other siblings. An agent is left to infer usage purely from the tool name and schema, which is insufficient for a choice among several expense-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete an existing expense by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The ID of the expense |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and readOnlyHint=false, indicating a destructive write operation. The description adds no further behavioral context beyond restating the action; it does not mention side effects, irreversibility, or the nature of the response. It does not contradict the annotations, so it meets the baseline but adds little value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that clearly communicates the action and target. It is front-loaded and contains no extraneous words, achieving appropriate brevity for a simple operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter delete operation with no output schema, the description covers the essential purpose and key parameter. It does not describe return values or error conditions, but these are often standard for delete operations and are not critical given the tool's simplicity. The description is complete enough for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully covers the single parameter 'id' with a description, and the tool description also mentions 'by ID', but adds no additional semantic detail beyond what the schema provides. With 100% schema description coverage, the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'delete an existing expense by ID' clearly states the action (delete) and the resource (expense), and specifies the identifier used. It is unambiguous and easily distinguishes from siblings like add_expense, update_expense, and list_expenses through the verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly conveys usage by the verb 'delete', but it does not explicitly state when to use it versus the alternatives, nor does it mention any constraints such as required existence or irreversibility. The context is clear enough for an agent to infer usage, but no explicit guidance or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get a spending summary
| Name | Required | Description | Default |
|---|---|---|---|
| month | No | A calendar month in YYYY-MM format |
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 fully covered and the bar is lower. The description adds only the marginal notion that this returns an aggregated summary, but does not disclose what gets aggregated or scoped. It does not contradict 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The phrase is four words with zero waste and a front-loaded verb, which is efficient. However, the brevity stems more from under-specification than from disciplined trimming, so it does not reach the level of a well-packaged, substance-complete definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with one optional parameter and annotations covering safety, this is a simple tool, but the description omits what the summary contains and what happens when month is omitted. With no output schema and no descriptive context, an agent still cannot predict the return shape or default time scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% — the single month parameter is fully documented with the description 'A calendar month in YYYY-MM format' and a regex pattern. Per the rubric, the baseline is 3 when the schema does the heavy lifting, and the description adds nothing beyond it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a verb ('get') and a resource ('spending summary'), and it distinguishes itself from the CRUD siblings (add/update/delete/list_expenses) as the aggregation view. However, it essentially restates the tool name ('get_spending_summary' → 'get a spending summary') and adds no new information about what the summary contains, so it sits at minimum viable rather than distinctly helpful.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to choose this tool vs its siblings. There is no mention of how a summary differs from list_expenses, when the optional month should be supplied, or what default scope applies if month is omitted. With four sibling tools, this leaves the decision entirely to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list expenses with optional filters
| Name | Required | Description | Default |
|---|---|---|---|
| month | No | A calendar month in YYYY-MM format | |
| category | No | The normalized expense category |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, so the tool is known to be safe. The description adds no behavioral context beyond 'list expenses'—nothing about pagination, sorting, default behavior (e.g., what happens if no filters are provided), or response format. Given annotations cover safety, the description fails to enrich the agent's understanding of how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence with no redundant words or filler. It is efficiently front-loaded with the core action ('list expenses') and the key feature ('optional filters'). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 optional params, no nested objects, no output schema) and strong annotations, the description is minimally adequate. However, it does not explain whether the filters can be combined, what the response looks like, or if there are limits. An agent would have to infer these from the schema and typical conventions. It is complete enough for a basic call but leaves room for ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both month and category are fully described in the schema. The description's phrase 'optional filters' adds no extra meaning about semantics like combined filtering or format. The baseline is 3 because the schema carries the full load; the description offers no additional insight.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists expenses and mentions optional filters, which maps to the parameters. It is distinct from the siblings (add/update/delete/spending summary) since 'list' is unambiguous. However, it does not explicitly name the filter dimensions (month, category) or contrast with the summary tool, so it's specific but not maximally differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 that get_spending_summary is for aggregated data, nor does it indicate that list_expenses is for raw expense details. The usage context is only implied by the verb 'list' and not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update an existing expense by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The ID of the expense | |
| date | No | The expense date in YYYY-MM-DD format | |
| amount | No | The expense amount, up to 1000000 | |
| category | No | The normalized expense category | |
| description | No | A short optional description of the expense |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=false, so the mutation nature is expected. The description adds that it updates an existing expense by ID, implying the target must exist. However, it does not disclose whether it performs a partial update (only provided fields) or a full replacement, nor what happens if the ID is not found. Given the annotations, the additional information is minimal but not contradictory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that front-loads the core action. There is no filler or redundant information. It earns its place with zero waste, making it exemplarily concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 5 parameters, no output schema, and only basic annotations, the description is insufficiently complete. It does not explain the update semantics (partial vs. full), error behavior for missing ID, or what the tool returns. While parameters are covered by the schema, key operational context is absent, leaving an agent to guess.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% since every parameter (id, date, amount, category, description) has its own description in the schema. The tool description adds no parameter-specific details beyond what the schema already provides. The baseline of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'update' and identifies the resource 'expense' and the key 'by ID'. It clearly distinguishes from sibling tools (add, delete, list, summary) by indicating this modifies an existing record. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, such as using add_expense for new expenses or delete_expense for removal. The description relies on the tool name and context, but does not explicitly state conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0add_expensedelete_expenseget_spending_summarylist_expensesupdate_expenseScored across 5 tools
Each tool has a clearly distinct purpose: add, update, delete, list, and summarize expenses. There is zero overlap, making it easy for an agent to select the right tool for the task.
All tools follow the consistent verb_noun pattern (add_expense, update_expense, delete_expense, list_expenses, get_spending_summary). This creates a predictable and uniform naming convention.
With only 5 tools, the server is tightly scoped for a personal expense tracker. Each tool serves a necessary function without unnecessary bloat, and the count is well within the ideal range.
The toolset covers full CRUD for expenses (add, update, delete, list) plus a summary function. A minor gap is the lack of a direct 'get_expense' by ID, but the list tool with filters can likely retrieve individual expenses, so it's a workable limitation.
Log, query, and edit expenses, budgets, and accounts in Manilo from any MCP-compatible AI assistant.
Log, query, and edit expenses, budgets, and accounts in Manilo (formerly Ledgy) from any MCP-compatible AI assistant.
Track expenses from your AI chat: log, categorize, monthly CSV reports. All data is local.
Log, query, and edit expenses, budgets, and accounts in Ledgy from any MCP-compatible AI assistant.
