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talonicdev/talonic-mcp

by Various

Official Talonic MCP server. Lets AI agents extract structured data from any document via the Model Context Protocol.

T

MCP

talonicdev/talonic-mcp

Added 1 June 2026

Overview

An official MCP server that enables AI agents to extract structured data from any document using the Model Context Protocol. It is built in TypeScript and provides a standardized interface for document parsing.

Best for

Best for
Developers building AI agents that need to extract structured data from unstructured documents

Use cases

  • Extract fields from invoices or receipts
  • Parse resumes into structured profiles
  • Pull key data from contracts or agreements

How to use

Install

npx -y @talonic/mcp@latest

Tools exposed

  • talonic_extract
  • talonic_request_upload
  • talonic_to_markdown
  • talonic_search
  • talonic_filter
  • talonic_get_document
  • talonic_list_schemas
  • talonic_save_schema
  • talonic_get_balance
  • talonic_get_pricing
  • talonic_get_usage

Tested with

Claude Desktop, Cursor, Cline, Continue, VS Code, JetBrains, Cowork, Claude.ai

Example client config

[object Object]

Notes

An official MCP server that enables AI agents to extract structured data from any document using the Model Context Protocol. It is built in TypeScript and provides a standardized interface for document parsing.

4 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Extract fields from invoices or receipts
  • Parse resumes into structured profiles
  • Pull key data from contracts or agreements

Pros

  • Leverages the Model Context Protocol for agent interoperability
  • TypeScript codebase for type safety and developer familiarity
  • Focused on structured data extraction from diverse document types

Cons

  • Low star count (4) suggests limited community adoption or maturity
  • Requires an MCP-compatible AI agent to function
  • Documentation and examples may be sparse

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Leverages the Model Context Protocol for agent interoperability
  • TypeScript codebase for type safety and developer familiarity
  • Focused on structured data extraction from diverse document types

Cons

  • Low star count (4) suggests limited community adoption or maturity
  • Requires an MCP-compatible AI agent to function
  • Documentation and examples may be sparse

Pairs with

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