talonicdev/talonic-mcp
by Various
Official Talonic MCP server. Lets AI agents extract structured data from any document via the Model Context Protocol.
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_extracttalonic_request_uploadtalonic_to_markdowntalonic_searchtalonic_filtertalonic_get_documenttalonic_list_schemastalonic_save_schematalonic_get_balancetalonic_get_pricingtalonic_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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