Akahu（ニュージーランドのオープンバンキング）データをClaudeのようなLLMエージェントに公開するMCPサーバーです。エージェントが銀行口座の一覧表示、投資保有資産の確認、分析用の取引履歴取得を行えるようにします。
ローカルのSQLiteキャッシュ（cache.db）が過去約90日分の取引履歴をディスク上に保持し、段階的に更新します。キャッシュのTTLは、Akahu Personalのアップストリーム更新頻度（1日1回）に合わせて24時間に設定されています。エージェントは任意のツールで force=True を渡すことで、これをバイパスできます。
list_accounts(force=False) — 残高を含む銀行口座/預金口座。Sharesightは除外されます。
get_share_holdings(force=False) — Sharesightポートフォリオ：合計価値、内訳（リターン/資本/通貨/配当）、および保有銘柄ごとの行。
list_transactions(account, start=None, end=None, limit=100, force=False) — ローカルキャッシュから特定の口座の取引履歴を取得します。キャッシュが24時間以上経過している場合は、先にAkahuから更新します。account はIDまたは名前の曖昧な部分一致で指定します。
Related MCP server: financy
まだインストールしていない場合は、uv をインストールしてください。
Akahu Personal App をセットアップします。これは、自分のAkahuアカウントに対して作成する無料のシングルユーザーアプリです。app_token（個人アプリのID）と、自分自身の user_token が取得できます。
プロジェクトのルートに .env ファイルを作成します：
AKAHU_USER_TOKEN=user_token_xxx
AKAHU_APP_TOKEN=app_token_xxxuv sync を実行して依存関係をインストールします。
動作確認：uv run python -m akahu_mcp.sync — 口座が表示され、最初の口座の取引履歴が取得されるはずです。
claude mcp add akahu --scope user -- uv --directory /absolute/path/to/akahu-mcp run akahu-mcp~/Library/Application Support/Claude/claude_desktop_config.json（macOS）または各プラットフォームの対応するファイルに追加します：
{
"mcpServers": {
"akahu": {
"command": "uv",
"args": ["--directory", "/absolute/path/to/akahu-mcp", "run", "akahu-mcp"]
}
}
}ホストがPATH上で uv を見つけられない場合は、`"uv
List the user's bank/depository accounts (excludes Sharesight, which has its own tool). Cached for 24h; pass force=True to refresh from Akahu.
| Name | Required | Description | Default |
|---|---|---|---|
| force | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 discloses caching (24h) and refresh mechanism (force=True), which is good for a read tool. It does not mention auth requirements or error cases, but the core behavior is transparent.
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?
Two sentences, front-loaded with purpose, then additional details. Every word earns its place, no fluff.
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 output schema exists (context signal), the description needn't explain return values. It covers purpose, scope, caching, and parameter usage. For a list tool with one optional parameter, this is complete.
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 has 0% parameter description coverage, so the description compensates by explaining the 'force' parameter: pass force=True to refresh from Akahu. This provides necessary semantics beyond the schema.
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 'bank/depository accounts' and explicitly excludes Sharesight, which is handled by a sibling tool. The verb 'list' and specific resource make the purpose 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?
The description tells when to use (for bank/depository accounts) and excludes Sharesight. It also explains caching behavior and how to refresh with force=True. It could explicitly mention alternatives (e.g., get_share_holdings for Sharesight) but the exclusion is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List transactions for a bank account, served from a local cache that keeps the last ~90 days. The cache is refreshed at most once per 24h (Akahu Personal only refreshes upstream daily); pass force=True to bypass the TTL.
Args: account: account id or fuzzy substring match against account name start: ISO date (YYYY-MM-DD), inclusive lower bound on transaction date end: ISO date (YYYY-MM-DD), inclusive upper bound limit: max rows to return (default 100, newest first) force: bypass the 24h cache TTL
| Name | Required | Description | Default |
|---|---|---|---|
| account | Yes | ||
| start | No | ||
| end | No | ||
| limit | No | ||
| force | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden. It discloses caching (last ~90 days, 24h refresh), force parameter effect, and default limit order. It does not cover error handling or edge cases, but the output schema exists for return format.
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 structured with the main sentence followed by bullet-like Args. It is slightly verbose but each sentence contributes essential information. The purpose is front-loaded.
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 5 parameters and output schema, the description covers caching, date range, limit, and force flag. It lacks mention of error handling or account not found, but is largely complete for a list tool.
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 0%, but the description thoroughly explains all five parameters: account (fuzzy match), start/end (ISO dates), limit (max rows, default 100), force (bypass cache). This adds substantial value beyond the bare schema.
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 action and resource: 'List transactions for a bank account'. The sibling tools (get_share_holdings, list_accounts) deal with distinct resources, eliminating confusion.
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 explains caching behavior and the force parameter to bypass TTL, giving context on when to use this tool. It does not explicitly exclude alternative tools, but the resource difference makes it clear.
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.
v0.1.0get_share_holdingslist_accountslist_transactionsScored across 3 tools
Each tool targets a distinct area: share holdings, bank accounts, and transactions. There is no overlap in purpose.
All tool names follow a consistent verb_noun pattern: get_share_holdings, list_accounts, list_transactions.
3 tools cover the core read-only functionalities for personal finance. While limited, it is appropriate for the server's scope.
The set covers accounts, transactions, and investments, but lacks operations like getting a single account detail or investment transactions, leaving some gaps.
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