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nicklee002e

docconv-mcp

by nicklee002e
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docconv-mcp

MCP server for Doc_Conv — convert PDF / Word / Excel / PowerPoint documents to Markdown, paid per conversion with USDC on Base via the x402 protocol (gasless, EIP-3009). No account, no API key: the agent signs a USDC payment and the service returns Markdown.

Why? Feeding formatted files (PDF/PPT/DOCX) straight into an LLM can cost 5–50× more tokens than the same content as Markdown. This lets an agent cheaply pre-convert documents before use.

Tools

  • estimate_conversion(file_path) — free price quote (pages, credits, priceUsdc, jobId, jobToken). No payment, no side effects.

  • convert_document(file_path, max_usdc=1.0, poll_seconds=300) — pays via x402 (rejects if the quote exceeds max_usdc) and converts. Returns inline markdown for text documents, or a downloadUrl (zip) when the document contains images.

Related MCP server: x402-md-mcp

Install

Published to PyPI as docconv-mcp. Run with uvx (no install) or pip install docconv-mcp.

Configuration (env)

Variable

Description

Default

DOC_CONV_AGENT_PK

Private key of the agent's Base wallet (must hold USDC). Signs x402 payments. Secret — never commit or share.

(required)

DOC_CONV_BASE_URL

Doc_Conv service base URL. Override only if self-hosting.

https://converter.crepe.fund

The wallet needs USDC on Base; gas is paid by the service's x402 facilitator (the agent needs no ETH). Pricing is by document size: 50 pages = 1 credit = 0.2 USDC (call estimate_conversion for the exact amount).

Claude Desktop / Claude Code (claude_desktop_config.json or .mcp.json)

{
  "mcpServers": {
    "doc-conv": {
      "command": "uvx",
      "args": ["docconv-mcp"],
      "env": { "DOC_CONV_AGENT_PK": "0x<your-agent-wallet-private-key>" }
    }
  }
}

Claude Code one-liner:

claude mcp add doc-conv -- env DOC_CONV_AGENT_PK=0x<key> uvx docconv-mcp

Example

"Convert ~/papers/report.pdf to Markdown."

The agent calls estimate_conversion to see the price (e.g. 0.3 USDC), then convert_document to pay via x402 and return the Markdown. If conversion fails, the paid credit is retained on the payer wallet for reuse.

⚠️ convert_document spends real USDC. Use max_usdc to cap per-call cost.

Links

License

MIT © CREPE Foundation

Available Tools

2 tools
convert_documentA

문서를 Markdown으로 변환한다. x402로 USDC를 자동 결제한다.

가격이 max_usdc를 넘으면 결제하지 않고 거부한다(비용 폭주 방지). 이미지가 없는 문서는 markdown 텍스트를, 이미지가 포함된 문서는 zip 다운로드 URL을 반환한다.

Args: file_path: 변환할 로컬 파일 경로. max_usdc: 허용 최대 결제액(USDC). 견적이 이보다 크면 결제하지 않는다. poll_seconds: 변환 완료를 기다리는 최대 초. Returns: paid, txHash, priceUsdc, status, 그리고 markdown(이미지 없을 때) 또는 downloadUrl+format(이미지 있을 때).

ParametersJSON Schema
NameRequiredDescriptionDefault
max_usdcNo
file_pathYes
poll_secondsNo

TDQS

A4.4/5.0
Behavior4/5

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

Discloses automatic USDC payment via x402, cost ceiling via max_usdc, and conditional return types. No annotations provided, but description compensates well. Could mention error/failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Structured with intro and Args list. Somewhat verbose due to bilingual text, but each sentence adds value. Could be tighter by removing 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?

Covers conversion, payment, cost control, output formats. No output schema but describes returns. Missing edge cases (e.g., errors, unsupported formats) but sufficient for typical use.

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?

All three parameters explained in plain language (Korean): file_path, max_usdc, poll_seconds. Adds meaning beyond schema, including defaults and purpose.

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 'converts' and resource 'document to Markdown', with specific behaviors (payment, conditional output). Distinguishes from sibling 'estimate_conversion' by being the execution tool.

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 implicit guidance: use when you want to convert with payment, reject if over max. Describes how output differs based on images. Lacks explicit when-not-to-use or direct sibling comparison.

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

estimate_conversionA

문서 변환 가격을 미리 확인한다(결제·변환 없음).

Args: file_path: 변환할 로컬 파일 경로(pdf/docx/xlsx/pptx). Returns: pages(페이지 상당), credits, priceUsdc(예 "0.3"), payTo, jobId/jobToken.

ParametersJSON Schema
NameRequiredDescriptionDefault
file_pathYes

TDQS

A4.6/5.0
Behavior5/5

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

No annotations provided, so the description carries full burden. It clearly states no payment or conversion occurs, and lists return values (pages, credits, price, etc.), making behavior transparent without 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?

The description is concise, front-loaded with purpose, and uses bullet points for arguments and returns. Every sentence serves a purpose with no wasted words.

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 only one parameter, no output schema, and no annotations, the description is quite complete. It explains return fields and file types. However, terms like 'credits' and 'payTo' could use more explanation for full context.

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?

The description adds file type hints (pdf/docx/xlsx/pptx) to the sole parameter 'file_path', which the schema lacks (0% coverage). This compensates for the schema gap, though additional format details could enhance 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 clearly states the tool's purpose: checking document conversion price without performing the conversion. It distinguishes itself from the sibling tool 'convert_document' by specifying no payment or conversion happens.

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 implies when to use (before converting) and that it's a dry run. While it doesn't explicitly state when not to use, the contrast with the sibling tool provides context. Could be more explicit about use cases.

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. Dates show when Glama detected each change.

  1. 2 tool updatesv1.0.1
    • First observedconvert_document
    • First observedestimate_conversion
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TDQS

A4.7/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: one estimates cost, the other performs conversion with payment. No overlap or ambiguity.

Naming Consistency5/5

Both tool names follow a consistent verb_noun pattern in snake_case (estimate_conversion, convert_document).

Tool Count5/5

The server is focused on document conversion with a clear two-step workflow (estimate then convert). Two tools are exactly right for this scope.

Completeness5/5

The server covers the essential lifecycle: estimate cost and perform conversion. No obvious gaps for the stated purpose of converting documents.

Maintenance

ActivitySlowing
ResponsivenessSyncing

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