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steamau

Beeswax Shares MCP Server

by steamau

Upload document

upload_document

Upload a PDF or CSV statement to extract and reconcile transaction lines against the ledger. Unmatched lines become pending proposals for review.

Instructions

Upload a local PDF or CSV (broker statement, contract note, dividend statement, annual tax statement) into the fund's document store. Reads the file from disk, base64-encodes it and posts it; the server then automatically extracts statement lines and reconciles them against the ledger — unmatched lines become pending proposals in the Review Queue. Use get_document afterwards to check extraction and match results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoDocument kind, e.g. "broker_statement", "contract_note", "dividend_statement" (default "broker_statement")
titleNoHuman-friendly title (defaults from the file)
fund_idYesFund ID (discover via whoami or list_funds)
file_pathYesAbsolute path to the local PDF or CSV file
period_endNoStatement period end as an ISO date, e.g. "2026-05-30"
content_typeNoMIME type override; inferred from extension (.pdf/.csv) if omitted
period_startNoStatement period start as an ISO date, e.g. "2026-05-30"
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description details the automatic extraction and reconciliation behavior, including creation of pending proposals. This adds significant value for agent decision-making.

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 concise sentences cover purpose, process, and post-usage guidance without any wasted words. Essential information is front-loaded.

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?

Given the complexity (7 params, no output schema), the description adequately covers behavioral side effects and next steps. However, it omits potential error cases or prerequisite checks, leaving minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 7 parameters have schema descriptions (100% coverage), so the description adds only marginal value over the schema (e.g., explaining file reading process). Baseline 3 is appropriate.

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 explicitly states the verb 'Upload' and the resource 'local PDF or CSV' with specific document types. It clearly distinguishes from siblings by mentioning downstream tool get_document, and no other upload tool exists among siblings.

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 advises using get_document after upload to check results, providing a clear post-usage guideline. While it doesn't explicitly contrast with alternatives like reconcile_document, the context is sufficient for most use cases.

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

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