"Sublime Text" matching MCP servers:

Extracts structured JSON data from unstructured text using predefined schemas for receipts, invoices, resumes, and emails. It allows users to transform messy text into organized data through built-in or custom-defined fields.

A simple and efficient MCP server that provides Base64 encoding and decoding functionality for both text and images with support for Data URL format.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

Enables AI assistants to discover and invoke 445 Salesforce Marketing Cloud Next, Data 360, and Data 360 Connect API endpoints, plus SOQL queries, object describe, REST exploration, org limits, and record/metadata CRUD, with shared OAuth authentication and safety gates.

A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.

Integrates with the Datalog Studio REST API to explore projects, tables, and assets within a workspace. It enables users to understand data schemas and upload plain text content directly for AI processing.

Enables AI agents to remove duplicate lines or table rows from text, with options for case sensitivity, trimming, column-based comparison, ordering, and header handling, returning cleaned text and counts.

Enables users to paste messy delimited text and receive a cleaned, structured table by detecting the delimiter, columns, and suspect rows, then returning normalized rows as JSON. It also supports exporting the results as an .xlsx file through a simulated conversational chat interface.

Enables conversion of PDFs, images, and messy text into schema-guaranteed JSON, with tools for schema inference, validation, and credit management.

Provides deterministic, stateless tools for common data work including JSON, CSV, text, encoding, hashing, IDs, date/time, and number statistics.

Enables AI agents to convert CSV text into JSON arrays with automatic delimiter detection and optional header-row handling, accessed through a pay-per-call x402 micropayment API.

A FastMCP server for data processing tasks including CSV, JSON, text analysis, and numeric statistics, enabling users to parse, summarise, filter, convert, and analyze data through MCP tools.

MCP server for querying procurement and inventory documents (invoices, purchase orders, etc.) via structured lookups, precomputed comparisons, and full-text search.

Classifies PDFs (text-based vs scanned vs image vs mixed), extracts text, and converts to clean Markdown over Streamable HTTP MCP. Supports remote PDFs via URL or base64, with optional page restriction and OCR fallback detection.

Enables environmental scientists to tidy PFAS lab files, screen results against two drinking-water guideline sets side by side, search public guidance with page-level citations, and check report text so every number traces back to its lab row or guideline page.

Enables an AI assistant to reliably read and chunk PDF/text documents, validate extracted JSON against a schema with full error paths, and save structured output—all confined to a single allowed directory.

Enables interaction with Telegram chat history, including text, photos, and documents, via the GramJS MTProto userbot. It provides tools for searching chats, syncing message history, and downloading media files for local analysis.

MCP server that exposes local Python scripts as tools for AI clients (e.g. Claude Desktop), enabling directory tree generation, Excel-to-text conversion, Python code extraction, and text file merging.

An MCP server for AddressPenny address validation that enables users to validate postal addresses, bulk-clean address lists, and extract addresses from unstructured text through Claude Desktop, Cursor, and other MCP-compatible agents.

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.