Skip to main content
Glama

Bankstatemently

by io.github.bankstatemently

Request Upload URL

request_upload

Mint a single-use upload URL for pushing a conversation-attached PDF to Bankstatemently before converting it. Use this ONLY when you have no other way to reference the attached file (no pdf_file/pdf_url equivalent for this host) — e.g. a code-execution sandbox that can see the file on disk but has no URL for it. Playbook: (1) check your sandbox's uploads/attachments directory first — if the file isn't there yet, the mount can lag behind the conversation; ask the user to re-attach or wait a moment and check again before calling this tool. (2) Call request_upload to get upload_url and upload_id. (3) PUT the raw PDF bytes to upload_url with header Content-Type: application/pdf, e.g.: curl -X PUT "<upload_url>" -H "Content-Type: application/pdf" --data-binary @<path-to-file>. (4) Once the PUT succeeds, call convert_statement with upload_id set to the same value — never pdf/pdf_url/pdf_file for this flow. The URL and token are single-use and expire quickly; call request_upload again for a fresh one if the PUT fails partway through — never retry a failed PUT against the same URL. If the PUT fails with a network error or a "host not allowed"-style denial, the sandbox is likely blocking outbound requests to api.bankstatemently.com — tell the user to add api.bankstatemently.com to their host's code-execution allowed-domains setting (on claude.ai: Settings → Capabilities → Code execution) and retry. To convert several statements at once, pass count (1-100) instead of calling this tool once per file: the response returns "uploads", an array of that many { upload_id, upload_url } pairs — PUT each file to its own upload_url, then make ONE convert_statement call with upload_ids set to every upload_id. Free to use — no credits consumed (conversion itself still costs credits, same as any other convert_statement call).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
uploadsNo
max_bytesNo
upload_idNo
expires_atNo
upload_urlNo

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint=false, destructive=false), the description discloses single-use expiry, never retrying a failed PUT against the same URL, the need to call again for fresh URLs, potential sandbox outbound-blocking, and allowed-domains configuration. It also clarifies cost implications (free to use, conversion still costs). Annotations add no contradiction.

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?

Although long, the description is well-structured with a numbered playbook, clear sections for alternatives, error handling, batching, and costs. Every sentence provides operational value for a complex workflow; no filler or 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?

Given the tool's complexity, the description covers purpose, preconditions, step-by-step usage, post-conditions (convert_statement), failure modes, batch handling, security settings, and cost. It even explains the response structure despite an output schema, making it self-contained and complete.

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 schema only defines 'count' with min/max and no description. The description fully explains count: 'To convert several statements at once, pass count (1-100)' and describes the resulting 'uploads' array and how to PUT each file. This adds substantial meaning beyond the bare schema.

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 'Mint a single-use upload URL for pushing a conversation-attached PDF to Bankstatemently before converting it' — a specific verb, resource, and scope. It clearly distinguishes this tool from siblings by stating 'Use this ONLY when you have no other way to reference the attached file' and explicitly names convert_statement as the follow-up.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use vs. alternatives: only when no pdf_file/pdf_url equivalent exists, with a concrete example (code-execution sandbox). It also tells when NOT to use it (check uploads directory first, ask user to re-attach) and gives a numbered playbook with error handling and retry guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Bankstatemently toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Core tools are cleanly separated by resource: statements, transactions, transfers, credits, and benchmark all have dedicated entry points. The five analytics tools (aggregate, group_by, compare, time_series, top_n) share metric/filter language, but their distinct output shapes and careful descriptions prevent major confusion, with only group_by vs. time_series/top_n occasionally overlapping.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern such as convert_statement, list_transactions, rate_statement, and dismiss_statement. The analytics tools (aggregate, compare, group_by, time_series, top_n) break that pattern, but they are still recognizable, consistently styled, and form a meaningful cluster.

Tool Count4/5

At 16 tools, this is slightly above the typical 3-15 well-scoped range, but the server covers a broad workflow: upload, conversion, retrieval, categorization, analytics, transfer matching, rating, credits, and benchmarking. Each tool maps to a distinct capability, so the count feels justified rather than bloated.

Completeness4/5

The tool surface covers the full statement lifecycle from upload and conversion through retrieval, categorization, analysis, rating, and dismissal, plus useful side capabilities like credits and benchmark evaluation. Minor gaps exist—no permanent deletion and no way to manually edit category mappings—but dismiss_statement and categorize_statement provide adequate workarounds.

Resources