monzo-mcp

by partymola

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.6.1
Disambiguation4/5
Most tools are clearly distinct (accounts, balance, pots, sync, spending), but monzo_list_transactions and monzo_search_transactions both query transactions with overlapping merchant search capabilities. Descriptions help clarify that one is for structured filters and the other for full-text search, so confusion is limited.
Naming Consistency3/5
The monzo_ prefix is consistent, but the pattern is mixed: list_, get_, search_ are verbs, while sync and spending break the verb_noun convention. monzo_spending is a noun phrase, and monzo_sync lacks an object, making the naming style inconsistent though still readable.
Tool Count5/5
Seven tools is well-scoped for a Monzo banking integration covering accounts, balance, pots, transactions, and spending analysis, plus sync. Each tool serves a clear purpose without redundancy or bloat.
Completeness4/5
The server covers the core read/analyze lifecycle (accounts, balance, pots, transactions, spending) and includes a sync mechanism for offline access. Missing single-item retrieval (e.g., get_transaction) or write operations, but these feel out of scope for a read-focused analysis tool.
Average 4.4/5 across 7 of 7 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 41 commits in the last 12 weeks
- Last stable release on August 9, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under GPL 3.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It notes the side effect of recording a balance snapshot, which is valuable. However, it doesn't disclose authentication needs, rate limits, or whether it's safe/read-only. The snapshot side effect is mentioned but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with bullet point for argument. No redundancy. Every sentence adds value. Extremely concise and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists (not shown but indicated), so return values are documented externally. Description mentions returns and side effect. For a simple read tool with one parameter, this is fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the tool description explains account_type as 'personal' or 'joint' with default 'personal'. This adds meaning beyond the raw schema, though it could be more precise (e.g., listing exact values as enum). Given only one parameter, it's sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get current balance for a Monzo account' and specifies return values (balance, spend today, currency) and side effect (records snapshot). It distinguishes from siblings like monzo_list_accounts or monzo_list_transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not use this tool. It doesn't mention alternatives or prerequisites. Usage is implied by the purpose description but lacks clear contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present. The description states it returns account details, but does not explicitly confirm it is read-only or disclose potential side effects. For a simple list, default behavior is assumed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, front-loaded with purpose and key return details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with an output schema, the description sufficiently explains what is returned (type and status), making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters: schema coverage is 100% trivially, and the description adds no param info (as none needed). Baseline of 4 is appropriate per rubric.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'List' and resource 'Monzo accounts', specifying returned details (type, status) that distinguish it from siblings like transaction or balance tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives are provided. Usage is implied from context, but the description lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses a notable side effect: 'Also records balance snapshots,' which is beyond the basic listing action. It does not mention auth or rate limits, but the side effect disclosure is valuable for a read-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: a one-line purpose, a concise args section, and a brief return/side-effect note. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential aspects: what it lists, the parameter, a return summary, and the side effect. Since an output schema exists, detailed return formatting is not required. It lacks edge-case/error handling details, but for a simple list tool this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, leaving account_type underdocumented. The description's 'Args' section explicitly defines valid values ('personal' or 'joint') and the default, fully compensating for the schema gap and adding semantic clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List all pots (savings buckets) for a Monzo account' with a specific verb ('List') and resource ('pots'), clarified by the parenthetical. This clearly distinguishes it from sibling tools like monzo_list_accounts and monzo_list_transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when you need pots) but does not explicitly mention alternatives or provide exclusion criteria. It lacks guidance on choosing this over other Monzo tools, so usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, describes key behaviors: fetches up to 11 months, automatic pagination, deduplication, and SCA constraint. Lacks mention of write behavior to local cache but is clear on sync operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise with intro and bulleted args. No fluff, every sentence adds value. Well-structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers sync behavior, parameters, and constraints. Output schema exists so return values are handled. Might be missing a note on caching effects but overall sufficient for complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant meaning beyond schema: explains account_type values and since parameter format, including ISO date/datetime, override behavior, and SCA window restriction. 0% schema coverage so description is essential.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states syncing transactions, balances, and pots from Monzo API to local cache, with specific verb and resource. Differentiates from sibling tools like monzo_list_transactions which do not sync.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context on when to use: handles pagination, deduplication, and fallback behavior. Mentions SCA window and parameter usage. Does not explicitly state alternatives but implies use for bulk sync vs. simple queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It richly describes that the tool uses a local cache, auto-syncs when stale, queries a synced database rather than the live API, and includes counterparty objects for bank transfers. It also discloses the response shape. This is strong, but lacks mentions of rate limits, error cases, or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening, behavioral notes, return format, and an argument list. Every sentence adds value, and the argument list is formatted for easy parsing. It is appropriately sized given the six parameters and the need to clarify the cache-based nature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, the description covers all essential aspects: purpose, data source, sync behavior, return shape, and every parameter. It is complete for an agent to invoke correctly, and the output schema backs the return format. No significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description provides thorough parameter semantics for all six parameters: types, defaults, formats, examples, and matching behavior. This fully compensates for the schema's lack of descriptions and adds concrete use guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List transactions from the local cache.' It also distinguishes itself from siblings like monzo_search_transactions by explicitly noting it queries the synced transaction database, not the live API, giving it a distinct scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides useful context about when to use the tool: it reads from the cached/synced database and auto-syncs if stale. It doesn't explicitly name alternative tools for live queries, but the 'not the live API' exclusion helps agents infer its appropriate use case. Clear context but lacks explicit alternative naming.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the auto-sync side effect, the behavior of account_type in results, and the detail flag's effect. This goes beyond a basic 'what' and informs the agent of important behavioral nuances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the purpose, and uses a structured Args block. Every sentence adds value, covering behavior, parameters, and output characteristics without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite multiple optional parameters and an output schema, the description covers the essential behavior: auto-sync, output characteristics (account_type echoing), and parameter effects. The presence of an output schema means return values need not be described, and the description is complete for invocation purposes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates. It provides format (YYYY-MM), examples for category, allowed values for account_type, and the effect of detail, making each parameter's meaning clear beyond the schema's bare titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes spending from cached Monzo transactions, using a specific verb ('Analyse spending') and resource. It distinguishes itself from sibling tools like list_transactions and search_transactions by focusing on aggregated spending analysis rather than raw transaction listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (cached transactions, auto-sync when stale) and implies when to use it (for spending summaries). It does not explicitly name alternatives or exclusions, but the distinction from sibling tools is evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it excels. It discloses auto-sync behavior, case-insensitive partial matching, which fields are searched, the return shape, and even the inclusivity/exclusivity of date parameters. This goes well beyond a basic tool description and gives the agent a thorough understanding of the tool's runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: a one-sentence purpose followed by two short behavioral notes, a return-format line, and a clean bullet-list of args. Every sentence earns its place—there is no fluff, and the most critical information (what it does) is front-loaded. This is a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, cached data, auto-sync), the description covers all essential aspects: search criteria, cache behavior, matching rules, return format, and parameter semantics. It even explains an edge case (account_type null when unfiltered). The output schema exists and the description does not over-explain return values, striking the right balance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's 'Args:' section explains every parameter with meaningful details: the meaning of 'query', valid values for 'account_type' ('personal' or 'joint'), date semantics for 'since' (inclusive) and 'before' (exclusive), and the default for 'limit'. This fully compensates for the minimal schema and adds context that the schema titles and defaults alone do not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Search cached transactions by merchant, counterparty (payee), description, or notes.' It clearly distinguishes this from sibling tools like monzo_list_transactions by focusing on search and cached data, and also states the return format and key behavior (auto-sync, case-insensitive matching), making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is for searching transactions by specific fields, with auto-sync if stale, and explains the matching semantics. However, it does not explicitly mention when not to use it or name alternative sibling tools (e.g., monzo_list_transactions) for cases where a full listing is needed. This is a minor gap, so 4 rather than 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![monzo-mcp MCP server](https://glama.ai/mcp/servers/partymola/monzo-mcp/badges/card.svg)](https://glama.ai/mcp/servers/partymola/monzo-mcp)

Score Badge

Copy to your README.md:

[![monzo-mcp MCP server](https://glama.ai/mcp/servers/partymola/monzo-mcp/badges/score.svg)](https://glama.ai/mcp/servers/partymola/monzo-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/partymola/monzo-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server