Click on "Install 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., "@Personal Expense Tracker MCP Add a coffee purchase of $4.50 to today's expenses."
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.
# Personal Expense Tracker MCP
Personal Expense Tracker MCP is a simple local MCP server for tracking personal expenses
It stores expense data in a local CSV file
The server gives an MCP client five focused tools
add a new expense
list saved expenses
create a spending summary
update an existing expense
delete an existing expense
The project is made to be simple and easy to run locally
No bank account or external API is needed
Related MCP server: expense-mcp
Before starting make sure you have these installed
Node.js version 20 or newer
npm
Git
Check Node.js
node --versionCheck npm
npm --versionCheck Git
git --versiongit clone https://github.com/MohammadYousef-001/Personal-Expenses-Tracker.gitcd Personal-Expenses-Trackernpm installWait until npm finishes installing the required packages
Expenses are stored locally in
data/expenses.csvThe CSV file uses these columns
id,amount,category,date,descriptionDo not change the column names
To start the server run
npm run devThe server uses standard input and output for MCP communication
It is a local server and does not need a web port
MCP Inspector is the easiest way to test the tools manually
Run
npm run inspectA browser window should open with MCP Inspector
If it does not open automatically use the URL shown in the terminal
In Inspector
connect to the server
open the Tools section
choose a tool
enter the input
click Execute Tool
check the result
Tool | What It Does | Main Inputs |
| adds a new expense to the CSV file | amount category date description |
| lists saved expenses and can filter them | month category |
| calculates spending totals for a month | month |
| updates one existing expense | id and at least one expense field |
| deletes one existing expense | id |
Use add_expense to save a new expense
amount
The amount of money spent
It must be a positive number
category
The expense category
Examples
groceries
transport
bills
shoppingThe category is stored in lowercase so category names stay consistent
date
The expense date
It must use
YYYY-MM-DDExample
2026-08-12The date must also be a real calendar date
This is invalid
2026-99-99description
Optional short information about the expense
{
"amount": 25,
"category": "groceries",
"date": "2026-08-12",
"description": "milk and bread"
}A successful request adds the expense to
data/expenses.csvUse list_expenses to view saved expenses
Without filters
{}Filter by category
{
"category": "groceries"
}Filter by month
{
"month": "2026-08"
}Use both filters
{
"month": "2026-08",
"category": "groceries"
}The month must use
YYYY-MMThe month must be between 01 and 12
This is invalid
2026-99Use get_spending_summary to see a summary of your spending
Example
{
"month": "2026-08"
}The result can include
selected month
total amount spent
number of expenses
total spending for each category
Example result
month: 2026-08
total amount: 150
expense count: 4
category totals:
groceries: 80
transport: 30
bills: 40The real values depend on the data inside data/expenses.csv
I spent 25 on groceries todayThis can use
add_expenseshow my grocery expenses for this monthThis can use
list_expenseshow much did I spend this monthThis can use
get_spending_summaryThe project checks tool input before using it
Examples of invalid input
negative amount
zero amount
wrong date format
impossible calendar date
invalid month
category that is too long
description that is too long
Invalid input is rejected before it is saved
Run
npm run check:schemaA successful result should show
All expense schemas are valid.If you see an error saying a package or module cannot be found run
npm installThen try again
npm run devMake sure the packages are installed
npm installThen run
npm run inspectIf an old Inspector process is still running press
Ctrl + CThen start Inspector again
Run
npm run check:schemaIf everything is correct you should see
All expense schemas are valid.If there is an error check the file name and line number shown in the terminal
Fix the error before starting Inspector again
A valid date must use
YYYY-MM-DDValid example
2026-08-12Invalid example
2026-99-99Check
data/expenses.csvMake sure it contains expense rows below the CSV header
If the file only contains the header then an empty result is normal
Important project files
Personal-Expenses-Tracker/
│
├── data/
│ └── expenses.csv
│
├── docs/
│ ├── design.md
│ └── threat-model.md
│
├── examples/
│
├── src/
│ ├── index.ts
│ ├── schemas/
│ ├── tools/
│ └── lib/
│
├── SECURITY.md
├── package.json
└── README.mdTool input is treated as untrusted input
The project validates input before important operations
The expense file path is controlled by the application
Errors returned to the MCP client are kept short
More detailed errors stay in the local terminal for debugging
The expense tools do not require external network requests
More security information is available in
SECURITY.mdThis project is a small local personal expense tracker
It does not include
bank account connections
automatic bank imports
user login
cloud database
full graphical application
financial forecasting
The main goal is to provide simple MCP tools for local expense tracking
This project uses the MIT License
See LICENSE
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. Dates show when Glama detected each change.
v0.1.0add_expensedelete_expenseget_spending_summarylist_expensesupdate_expenseEach 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.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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.
Log, query, and edit expenses, budgets, and accounts in Ledgy from any MCP-compatible AI assistant.
Personal finance tracker — log transactions, view summaries, and browse a dashboard
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