Lunch Money MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Lunch Money MCP Servershow my recent transactions"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Lunch Money MCP Server
A Model Context Protocol (MCP) server that enables AI agents to interact with your Lunch Money personal finance data.
Features
This MCP server exposes 15 tools for managing your financial data:
User & Account
get_user— Get your profile and account information
Categories
get_categories— List all categories (flattened or nested)create_category— Create new custom categoriesupdate_category— Modify existing categories
Transactions
get_transactions— Query transactions with filters (date range, category, status, etc.)create_transaction— Add new transactions (single or batch up to 500)update_transaction— Update transactions or split them into multiple entries
Assets & Accounts
get_assets— List manually managed assetscreate_asset— Add new manual assetsget_plaid_accounts— List Plaid-connected bank accountstrigger_plaid_fetch— Trigger Plaid account sync
Budgets & Planning
get_budgets— View budgets and spending for any date rangeupsert_budget— Set or update budget amountsget_recurring_items— View recurring expenses and income
Tags
get_tags— List all transaction tags
Related MCP server: YNAB Assistant
Prerequisites
Node.js 18 or newer
A Lunch Money account with API access
A Lunch Money API key from the developers page
Installation
Option 1: Clone and Build (Local stdio transport)
For local use with Cursor, Claude Desktop, or other stdio-based MCP clients:
# Clone the repository
git clone https://github.com/yourusername/lunchmoney-mcp.git
cd lunchmoney-mcp
# Install dependencies
npm install
# Build the TypeScript
npm run buildOption 2: Cloudflare Workers (Remote HTTP transport)
Deploy as a remote MCP server accessible via HTTP:
# Clone the repository
git clone https://github.com/yourusername/lunchmoney-mcp.git
cd lunchmoney-mcp
# Install dependencies
npm install
# Set your API key as a secret
npx wrangler secret put LUNCH_MONEY_API_KEY
# Enter your Lunch Money API key when prompted
# Deploy to Cloudflare Workers
npm run deployOption 3: Use with npx (Local only)
You can run the MCP server directly without cloning:
npx -y lunchmoney-mcpNote: You'll still need to set the LUNCH_MONEY_API_KEY environment variable.
Configuration
Getting Your API Key
Log in to Lunch Money
Go to Settings → Developers
Generate a new API key
Copy the key (keep it secure!)
Cursor IDE
Add to your Cursor MCP configuration (~/.cursor/mcp.json):
{
"mcpServers": {
"lunchmoney": {
"command": "node",
"args": ["/path/to/lunchmoney-mcp/dist/index.js"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}Or with npx:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["-y", "lunchmoney-mcp"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}Claude Desktop
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"lunchmoney": {
"command": "node",
"args": ["/path/to/lunchmoney-mcp/dist/index.js"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}Other MCP Clients
Any MCP client that supports stdio transport can use this server. Set the LUNCH_MONEY_API_KEY environment variable and run:
node /path/to/lunchmoney-mcp/dist/index.jsRemote MCP via Cloudflare Workers (BYO API Key)
The Cloudflare Workers deployment is designed as a public MCP server where each user brings their own API key. The server never stores any API keys.
How it works:
Deploy the server to Cloudflare Workers (or use a shared instance)
Each user connects with their own Lunch Money API key
The API key is sent with each request in the
X-LunchMoney-API-Keyheader
Connecting with mcp-remote proxy:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["mcp-remote", "https://lunchmoney-mcp.your-subdomain.workers.dev/mcp"],
"env": {
"MCP_HEADERS": "X-LunchMoney-API-Key: your_api_key_here"
}
}
}
}Note: The mcp-remote proxy must support custom headers. Some MCP clients may not support this yet.
⚠️ Treat your
mcp.jsonfile like a credentials file. It now contains your Lunch Money API key. Never commit it to a Git repository (including dotfiles repos). Add it to.gitignoreif it lives inside one. Anyone with read access to this file can read and modify your Lunch Money data.
Security: This is the most secure model because:
The server never stores any API keys
Each user only accesses their own data
API keys are passed per-request, not stored on the server
The public worker enforces per-IP rate limiting and never logs request bodies or headers
Cloudflare Workers Deployment (Public Server)
This creates a public MCP server that anyone can use with their own API key. The server doesn't store any credentials.
Prerequisites
A Cloudflare account (free tier works)
Wrangler CLI installed
Deploy
Install dependencies:
npm installDeploy to Cloudflare Workers:
npm run deployYour public MCP server is now live! The URL will be shown in the output:
https://lunchmoney-mcp.your-account.workers.dev/mcpOptional: You can set a default API key for testing:
npx wrangler secret put LUNCH_MONEY_API_KEYHow Users Connect
Users connect to your public server with their own Lunch Money API key:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["mcp-remote", "https://lunchmoney-mcp.your-account.workers.dev/mcp"],
"env": {
"MCP_HEADERS": "X-LunchMoney-API-Key: their_api_key_here"
}
}
}
}Local Development with Wrangler
# Run locally with hot reload
npm run dev:workerSecurity Model
Server never stores API keys — keys are passed per-request via header
Users only access their own data — each request uses the user's own key
Publicly accessible — anyone can use the server, but they need their own Lunch Money account
This is similar to how public API gateways work — the infrastructure is shared, but credentials are per-user.
Usage Examples
Once configured, you can ask your AI assistant questions like:
"Show me my spending by category this month"
"What was my largest expense last week?"
"Categorize all my uncategorized transactions from March"
"Create a new category called 'Freelance Income'"
"How much did I spend on groceries in Q1?"
"List all my recurring subscriptions"
Development
Local stdio mode (for Cursor, Claude Desktop)
# Install dependencies
npm install
# Run in development mode with hot reload
npm run dev
# Build for production
npm run build
# Type check without emitting
npm run typecheck
# Test with MCP Inspector
npm run inspectCloudflare Workers mode (for remote HTTP access)
# Build the Worker
npm run build
# Run locally with Wrangler
npm run dev:worker
# Deploy to production
npm run deployProject Structure
src/
├── index.ts # MCP server entry point (stdio mode)
├── worker.ts # Cloudflare Workers entry point (HTTP mode)
├── client.ts # Lunch Money API client
├── types.ts # TypeScript type definitions
├── tool-utils.ts # Shared tool utilities
└── tools/ # Individual tool implementations
├── user.ts
├── categories.ts
├── transactions.ts
├── assets.ts
├── plaid.ts
├── budgets.ts
├── recurring.ts
└── tags.tsDeployment Modes
Mode | Transport | Use Case | Entry Point |
Local | stdio | Cursor, Claude Desktop |
|
Cloudflare Workers | Streamable HTTP | Remote access, web clients |
|
Both modes share the same tool implementations and API client.
Security
API Key Protection
Never commit your API key. The
.envfile is in.gitignorefor this reason.Store your key in environment variables or secure MCP configuration files.
If your key is exposed, revoke it immediately at Lunch Money Developers and generate a new one.
Data Privacy
This server acts as a proxy between your AI assistant and Lunch Money.
Your financial data is processed according to Lunch Money's privacy policy.
Error messages are sanitized to prevent accidental information disclosure.
Permissions
The API key you provide determines what actions the MCP server can perform. Lunch Money API keys can:
Read all your financial data
Create, update, and delete transactions
Modify categories and budgets
Trigger Plaid syncs
API Reference
This MCP server uses the Lunch Money API v1.
Rate Limits
The Lunch Money API has rate limits. The MCP server will pass through any rate limit errors from the API. If you encounter rate limiting, wait a few minutes before trying again.
Error Handling
The server handles Lunch Money API errors and returns them as MCP tool errors. Some notes:
Lunch Money sometimes returns logical errors as HTTP 200 responses — these are normalized into proper errors
The server sanitizes error messages to remove potential sensitive information
Full error details are logged to stderr for debugging
Troubleshooting
"Missing LUNCH_MONEY_API_KEY" error
The LUNCH_MONEY_API_KEY environment variable is not set. Check your MCP configuration and ensure the key is properly configured.
"Unauthorized" error
Your API key may be invalid or revoked. Verify your key at https://my.lunchmoney.app/developers
Transactions not appearing
If you use Plaid-connected accounts, you may need to trigger a sync:
Use the
trigger_plaid_fetchtool to queue a background syncNote that this only queues the job — it may take a few minutes for transactions to appear
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Fork the repository
Create your feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'feat: add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
License
This project is licensed under the ISC License — see the LICENSE file for details.
Acknowledgments
Built with the Model Context Protocol SDK
Powered by Lunch Money
Support
For issues with this MCP server, please open a GitHub issue
For Lunch Money API questions, see the Lunch Money API docs
For MCP protocol questions, see the MCP documentation
Disclaimer: This is an unofficial community project. It is not affiliated with or endorsed by Lunch Money.
Available Tools
15 toolscreate_assetC
Create a manually managed asset in Lunch Money.
| Name | Required | Description | Default |
|---|---|---|---|
| type_name | Yes | ||
| subtype_name | No | ||
| name | Yes | ||
| display_name | No | ||
| balance | Yes | ||
| balance_as_of | No | ||
| currency | No | ||
| institution_name | No | ||
| closed_on | No | ||
| exclude_transactions | No |
TDQS
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. The single sentence only states the action, omitting any details about side effects, required permissions, rate limits, or response behavior. This is critically insufficient for a creation tool.
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, grammatically correct sentence. However, it is too brief to be useful; conciseness should not come at the cost of essential information. It could be expanded while remaining 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?
Given the tool's complexity (10 parameters, no output schema, and no annotations), the description is extremely incomplete. It fails to explain the concept of a 'manually managed asset', how it fits into the Lunch Money system, or what the return value would be. The agent would struggle to use this tool 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 input schema has 10 parameters with 0% schema description coverage, meaning the names and types are the only clues. The description adds no explanation of parameter meanings, constraints, or relationships. For example, 'balance' is required but its format or default currency is not clarified.
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 verb ('create') and the resource ('manually managed asset'), and it distinguishes from sibling tools like 'create_category' which deal with different entities. However, it could be more specific about what constitutes a 'manually managed asset' in Lunch Money.
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, nor does it mention any prerequisites or scenarios where it should not be used. This lack of context forces the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_categoryC
Create a new Lunch Money category.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| description | No | ||
| is_income | No | ||
| exclude_from_budget | No | ||
| exclude_from_totals | No | ||
| archived | No | ||
| group_id | No |
TDQS
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 only states 'Create a new...', which implies a write operation but does not mention side effects, authentication needs, or whether the operation is idempotent. For a mutation tool, this is minimal transparency.
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 immediately states the purpose. It is front-loaded and efficient, with no extraneous words. However, it is too brief and sacrifices informativeness for brevity.
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 complexity (7 parameters, no output schema, no annotations), the description is incomplete. It does not explain how parameters like 'group_id' or 'archived' affect the behavior, nor does it describe the return value or success indicators. More context is needed for effective use.
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 has 7 parameters with 0% description coverage, meaning the description adds no explanation for any parameter. The description does not compensate for the lack of schema descriptions. It does not clarify the meaning of 'is_income', 'exclude_from_budget', etc., which are non-obvious. The baseline is low due to low 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 clearly states the action ('Create') and the resource ('a new Lunch Money category'), specifying the verb and object. It distinguishes from sibling tools like 'update_category' and 'get_categories' by implying the creation operation. However, it lacks additional context such as the domain or scope.
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. There is no mention of prerequisites, such as requiring an existing group_id, or when to use 'update_category' instead. The name and siblings imply a create operation, but no explicit context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_transactionC
Create one or more Lunch Money transactions.
| Name | Required | Description | Default |
|---|---|---|---|
| transactions | Yes | ||
| apply_rules | No | ||
| skip_duplicates | No | ||
| check_for_recurring | No | ||
| debit_as_negative | No | ||
| skip_balance_update | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fails to disclose any behavioral traits (e.g., idempotency, duplicate handling, balance update effects) beyond what is minimally implied by 'Create'. No annotations are present to compensate.
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 concise (one sentence) and front-loaded with the purpose. However, it lacks any structure or additional sections, which is acceptable given the single sentence.
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 complexity of the input schema (many parameters, nested objects) and the absence of annotations and output schema, the description is severely incomplete. It does not explain return values, error cases, or any behavioral details.
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 0%. The description adds no meaning to the many parameters, such as apply_rules, debit_as_negative, or skip_duplicates, leaving their semantics entirely to 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 verb 'Create' and the resource 'one or more Lunch Money transactions', which distinguishes it from sibling tools like update_transaction and get_transactions.
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 provided on when to use this tool versus alternatives such as update_transaction, nor are there any prerequisites or constraints mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_assetsARead-only
List manually managed Lunch Money assets.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's minimal addition of 'manually managed' provides some extra context about the type of assets, but it doesn't contradict annotations or add significant behavioral traits.
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?
Single short sentence with no waste; perfectly front-loaded and to the point.
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 simple listing tool with no parameters and a readOnly annotation, the description provides adequate context, including the asset type (manually managed). No output schema exists, but the tool's behavior is straightforward.
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?
Input schema has no parameters and is fully covered (100%). Description adds value by specifying 'manually managed', which clarifies the scope beyond the empty 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?
Description uses specific verb 'List' and clearly identifies the resource as 'manually managed Lunch Money assets', distinguishing it from siblings like get_plaid_accounts and create_asset.
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 explicit guidance on when to use or when not to use this tool versus alternatives. However, the purpose is clear enough that an agent can infer it's for listing only manual assets, not Plaid accounts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_budgetsARead-only
Get Lunch Money budgets and spending for a date range.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| end_date | Yes | ||
| currency | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds that it returns both budgets and spending, providing context beyond the annotation. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. It is concise but could benefit from slightly more detail without sacrificing brevity.
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?
The description covers purpose and basic output, but lacks parameter explanations and output schema details. For a 3-parameter tool with no output schema, it provides adequate but not comprehensive 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?
Schema coverage is 0%: the description does not explain any parameter. While 'date range' hints at start_date/end_date, it omits details on format, optional currency, and usage.
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 'Get' and the resource 'Lunch Money budgets and spending', specifying a date range. It effectively distinguishes from sibling tools like upsert_budget, which is for modifications.
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 implies use when retrieving budget data for a date range but provides no explicit guidance on when to avoid this tool or mention alternatives like upsert_budget.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_categoriesARead-only
List Lunch Money categories in flattened or nested form.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so description's value is limited. It adds the format choice but lacks details on response structure, pagination, or ordering.
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?
Single sentence, front-loaded with verb and resource, no unnecessary words. Highly efficient.
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 simple read-only list tool with one optional enum parameter, the description covers the core function and parameter. Lacks mention of output structure, but adequate given simplicity and lack of output schema.
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 single parameter 'format' has an enum, and the description explains its two values ('flattened or nested'), adding meaning beyond the schema (which has 0% description 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 clearly states the verb 'List' and the resource 'Lunch Money categories', and distinguishes its output format options ('flattened or nested') from sibling tools like create_category or update_category.
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 on when to use this tool versus similar list tools (e.g., get_assets, get_tags). No mention of use cases, limitations, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_plaid_accountsARead-only
List Lunch Money Plaid-connected accounts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description adds no further behavioral details (e.g., data freshness, pagination, or authentication requirements). It simply repeats the read-only nature implied by the annotation.
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, clear sentence with no wasted words. It is concise but could benefit from a bit more detail without becoming verbose.
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 parameterless list tool, the description is adequate but lacks context about potential prerequisites (e.g., Plaid link requirement) or relationship to sibling tools like trigger_plaid_fetch. No output schema exists, but the simplicity of the tool reduces the need for extensive documentation.
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?
There are no parameters in the input schema, so the description does not need to elaborate on parameter meaning. The baseline is 4 for zero-parameter tools.
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 the specific verb 'List' and identifies the resource as 'Lunch Money Plaid-connected accounts,' clearly distinguishing it from sibling tools like get_assets or get_categories.
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 does not provide explicit usage guidance, such as when to use this tool versus alternatives like trigger_plaid_fetch. The purpose is clear, but no context on prerequisites or limitations is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recurring_itemsARead-only
Get Lunch Money recurring items for the current or specified month range.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | No | ||
| end_date | No | ||
| debit_as_negative | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as readOnlyHint=true, and the description aligns with a read operation. Beyond that, no additional behavioral traits (e.g., rate limits, data freshness) are disclosed. The description adds minimal extra context.
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 sentence of 12 words, front-loaded with the key action and resource. Every word earns its place with no redundancy.
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 has 3 parameters and no output schema, the description covers the core purpose but omits details on the debit_as_negative parameter and response format. It is adequate for low complexity but not fully 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?
Schema description coverage is 0% with 3 parameters. The description hints at start_date/end_date via 'month range' but does not explain debit_as_negative or provide format details. It fails to compensate for low 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 clearly states the verb 'Get' and resource 'Lunch Money recurring items' with scope 'current or specified month range', distinguishing it clearly from sibling tools like get_transactions and get_budgets.
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 implies usage for month ranges but provides no explicit guidance on when to use this tool versus alternatives such as get_transactions or get_budgets. No exclusions or comparison are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tagsARead-only
List all Lunch Money tags.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, confirming it's a read operation. The description adds the scope 'all', which is useful context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence of four words, perfectly front-loaded and without any wasted words.
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?
While the description is adequate for a simple list tool with no parameters, it lacks information about the return format or fields of the tags. Without an output schema, the description should provide more detail.
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?
No parameters exist in the schema (100% coverage), so baseline is 4. The description does not need to add parameter information.
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 'List' and resource 'tags', clearly stating it returns all tags. This distinguishes it from sibling tools that deal with other resources.
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 explicit guidance on when to use versus alternatives. Since there are no sibling tag tools, usage is implied, but no exclusions or when-not-to-use are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transactionsCRead-only
Get Lunch Money transactions with optional filters.
| Name | Required | Description | Default |
|---|---|---|---|
| tag_id | No | ||
| recurring_id | No | ||
| plaid_account_id | No | ||
| category_id | No | ||
| asset_id | No | ||
| is_group | No | ||
| status | No | ||
| start_date | No | ||
| end_date | No | ||
| debit_as_negative | No | ||
| pending | No | ||
| offset | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While annotations indicate readOnlyHint=true (safe read), the description does not add any behavioral details beyond the obvious. It omits information about pagination, data format, or potential limits.
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 one sentence and concise, but it is too minimal for the complexity of 13 parameters. It is front-loaded but lacks useful structure or breakdown.
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 has 13 optional parameters and no output schema, the description does not provide enough context about typical usage, required constraints (e.g., date range), or how filtering works. The agent might miss important behaviors like pagination defaults.
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 0%, and the description only says 'optional filters' without explaining any of the 13 parameters. The agent receives no additional meaning over parameter names, some of which (e.g., debit_as_negative, is_group) are not self-explanatory.
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 verb 'Get' and the resource 'Lunch Money transactions', and mentions optional filters. It is unambiguous and distinguishes from sibling tools like create_transaction or update_transaction by its name and verb.
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 provided on when to use this tool vs. alternatives (e.g., create_transaction for adding, update_transaction for modifying). The agent must infer from context or tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_userARead-only
Get information about the Lunch Money user connected to the configured API key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint true. The description confirms it's a read operation without adding behavioral details beyond that. It does not specify what specific information is returned or any 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is clear and front-loaded. No unnecessary words or repetition.
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?
The description lacks detail about the return structure. With no output schema, the description should elaborate on what 'information' is returned. It is minimally complete but not comprehensive.
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 zero parameters, and schema coverage is 100%. The description does not need to add parameter semantics. Baseline score of 4 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 clearly states it retrieves information about the Lunch Money user. The verb 'Get' and resource 'information about the Lunch Money user' are specific, and no sibling tool overlaps in purpose.
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 explicit guidance on when or when not to use this tool. Since there are no similar siblings, the usage context is implied, but the description does not provide any prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trigger_plaid_fetchC
Trigger a Lunch Money fetch for eligible Plaid accounts. This queues a background fetch job.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | No | ||
| end_date | No | ||
| plaid_account_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It notes the job is queued (async), but does not disclose safety, auth requirements, rate limits, or what happens if a fetch is already in progress.
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 are concise, but the description is too brief for a tool with 3 parameters and no output schema. It could be structured better with a brief parameter explanation.
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 complexity (3 params, no output schema, no annotations), the description lacks details on return value, error handling, or behavior when fetch is already queued. It is incomplete for safe invocation.
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 has 3 optional parameters with 0% description coverage. The description does not explain any parameter, leaving the agent to guess their purpose (e.g., date range or account filter).
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?
Description clearly states the action (trigger fetch) and target (eligible Plaid accounts). It mentions queuing a background job, which adds context. However, it does not define 'eligible', which could confuse the agent.
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 on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., account must be linked) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_categoryC
Update an existing Lunch Money category.
| Name | Required | Description | Default |
|---|---|---|---|
| category_id | Yes | ||
| name | No | ||
| description | No | ||
| is_income | No | ||
| exclude_from_budget | No | ||
| exclude_from_totals | No | ||
| archived | No | ||
| group_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only says 'update' without disclosing return behavior, idempotency, or authentication requirements.
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, but it is too brief and lacks any structuring (e.g., sections, bullet points).
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 8 parameters and no output schema, the description is severely incomplete. It fails to explain what the tool returns or any side effects.
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 0%, and the description adds no meaning to any of the 8 parameters. Parameters are completely undocumented.
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 verb 'update' and the resource 'category', distinguishing it from create_category and get_categories. However, it lacks specifics on which fields can be updated, but 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 on when to use this tool versus alternatives like create_category. No conditions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_transactionC
Update a Lunch Money transaction or split it into multiple child transactions.
| Name | Required | Description | Default |
|---|---|---|---|
| transaction_id | Yes | ||
| transaction | No | ||
| split | No | ||
| debit_as_negative | No | ||
| skip_balance_update | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but does not disclose whether updates are partial or full, what happens to existing data, balance implications, or the behavior of splitting. This is a significant gap 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure to cover both operations (update and split). It is adequately short but sacrifices necessary 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?
Given the complex input schema and no output schema, the description is severely incomplete. It does not explain return values, error handling, or behavioral details essential for effective use.
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 0%, and the description provides no explanation of parameters. The complex nested objects 'transaction' and 'split' are completely undocumented, leaving the agent without guidance on how to structure the input.
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 ('Update') and the resource ('a Lunch Money transaction'), and includes the special capability ('split it into multiple child transactions'). This differentiates it from siblings like create_transaction and get_transactions effectively.
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 provided on when to use this tool versus alternatives, nor when splitting is appropriate. There are no prerequisites or contextual conditions mentioned, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upsert_budgetC
Create or update a Lunch Money budget entry for a category and month.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| category_id | Yes | ||
| amount | Yes | ||
| currency | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'Create or update', implying a write operation, but provides no details on side effects (e.g., overwriting existing budgets), return values, or required permissions. Behavioral traits are severely under-disclosed.
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 immediately conveys the core purpose. It is front-loaded with the action and resource. However, it lacks any structure (e.g., sections) that could improve scannability for an AI agent.
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 no output schema, the description should at least hint at return format or behavior. It mentions 'budget entry for a category and month' but doesn't confirm that start_date should be the first day of the month or that category_id comes from get_categories. The presence of sibling tools like get_budgets for reading is not referenced. Completeness is low.
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 0%, yet the description adds no parameter information. It fails to explain what start_date, category_id, amount, or currency represent or their constraints (e.g., start_date should be first of month). The description adds zero value beyond the raw 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 verb 'Create or update' and the resource 'Lunch Money budget entry', and specifies the context 'for a category and month'. This distinguishes it from sibling tools like create_category or get_budgets, which involve different resources or actions.
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 provided on when to use this tool versus alternatives or when not to use it. For example, it doesn't clarify that the upsert replaces existing budgets for the same category and month, or that get_budgets should be used for reading. The description lacks any comparative context.
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.
15 tool updates
v1.0.0- First observed
create_asset - First observed
create_category - First observed
create_transaction - First observed
get_assets - First observed
get_budgets - First observed
get_categories - First observed
get_plaid_accounts - First observed
get_recurring_items - First observed
get_tags - First observed
get_transactions - First observed
get_user - First observed
trigger_plaid_fetch - First observed
update_category - First observed
update_transaction - First observed
upsert_budget
TDQS
Scored across 15 tools
Each tool targets a distinct resource or action, with clear separation between asset, category, transaction, budget, account, recurring item, tag, and user operations. No overlapping functionality.
All tools follow a consistent verb_noun pattern (e.g., create_asset, get_transactions, update_category), using the same set of verbs (create, get, update, upsert, trigger) throughout.
With 15 tools, the server covers the core aspects of personal finance management without being overloaded or underdeveloped. Each tool has a clear purpose.
The server provides create, read, and update operations for several resources, but lacks delete operations for all resources and missing update for assets and recurring items. Tags only have a get operation, leaving significant gaps in the lifecycle.
Maintenance
Related MCP Connectors
Read-only Lunch Money accounts, transactions, categories and budgets. Unofficial connector.
Personal-finance workspace for AI agents: accounts, spending, budgets, goals, and investments.
- BankSyncOAuthio.banksync
Connect AI agents to bank accounts, transactions, balances, and investments.
- Era ContextOAuthapp.era
Personal finance, bank account, and shared memory connector for Claude, ChatGPT, Gemini Spark & more
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