Document & FinTech Parser MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| BASE_RPC_URL | Yes | Base L2 RPC URL used for verifying payments, e.g. https://mainnet.base.org. | |
| PAYMENT_WALLET | Yes | Recipient payout wallet address for x402 USDC micropayments on Base L2. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pdf_table_stream_extractor_resilientA | Extracts multi-page financial tables from complex PDFs with merged cells, ruled/unruled borders, and wrapped column baselines without misaligning cells. (0.040 USDC on Base L2) |
| pdf_page_rasterizer_highresA | Rasterizes complex vector PDF pages into crisp, 300 DPI antialiased WebP/PNG images optimized for multi-modal vision LLMs with zero text clipping. (0.035 USDC on Base L2) |
| ocr_bounding_box_dewarp_repairA | Performs geometric perspective dewarping for photographed and scanned paper documents, correcting camera skew, tilt, and binding curvature. (0.035 USDC on Base L2) |
| pdf_form_xfa_acroform_flattenerA | Flattens interactive AcroForms and dynamic XML XFA forms into static, immutable PDF pages with 100% field content preservation for optical validation. (0.035 USDC on Base L2) |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool performs a distinct operation on documents: table extraction, page rasterization, dewarping/repair, and form flattening. Boundaries are clear from the descriptions, though the rasterizer vs. table extractor split (both PDF-reading, output-different) requires reading descriptions to pick correctly.
All four names are snake_case with a consistent pattern of domain prefix + operation + qualifier (pdf_table_stream_extractor_resilient, pdf_page_rasterizer_highres). Minor deviation: one uses an 'ocr_' prefix instead of 'pdf_', and names are unusually verbose.
Four tools is lean but reasonable for a specialized document-parsing pipeline where each tool handles a distinct transformation. It sits at the low end, leaving little room for composition flexibility.
Covers table extraction, rasterization, dewarping, and form flattening, but a 'Document & FinTech Parser' would be expected to also offer plain text/content extraction, metadata or key-value parsing, and format conversion. Agents needing raw text or structured JSON output would hit a dead end.