DJAI Tools MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@DJAI Tools MCP Count tokens in this file and generate RAG chunks"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI Agent MCP Tool for Local Document, PDF, PNG/Image, QR, RAG, CSV & File Processing
English · ภาษาไทย · Try the original browser tools · Tool reference · Roadmap
Since publishing our free browser-based PDF tools, image converter and compressor, Thai-English OCR, DOCX converter, QR generator, AI token/RAG utilities, and CSV/JSON/Excel tools, many people have asked how they could let their AI or coding agents access that tool bundle and do the work for them. DJAI Tools MCP is our answer: a free, open-source, local-first Model Context Protocol server that gives AI agents carefully controlled file-processing capabilities on the user's own computer.
The goal is to help ChatGPT-compatible agents, Claude, Codex, Cursor, VS Code agents, and other MCP clients prepare context, count tokens, create RAG chunks, clean CSV/JSON data, generate QR files, and—through staged releases—process PDF, DOCX, OCR, PNG, JPG, WebP, images, and spreadsheets without sending private documents to DJAI.
Current release scope:
v0.1.0contains eight tested text, RAG, CSV, JSON, and QR tools. PDF conversion, DOCX, OCR, PNG/JPG image processing, and XLSX tools are published in our existing browser-tool collection and are planned for later MCP phases; they are not falsely advertised as working MCP commands in this release.
Why we built this
Browser tools are useful when a person wants to open a page and process a file. An MCP server serves a different workflow: the user asks an agent to prepare context, clean data, generate an artifact, or perform a multi-step task, and the agent calls narrowly described tools on the user's behalf.
This project is designed to provide:
Local privacy: files are read and processed on the user's machine.
Agent access: MCP-compatible agents can discover and call enabled tools.
Controlled permissions: the server reads and writes only inside allowed directories.
Repeatable workflows: structured results report paths, sizes, counts, warnings, and processing time.
Smaller tool menus: profiles register only the capabilities an agent needs.
Open development: source code is free under the MIT License and welcomes community review.
No DJAI processing bill: users provide their own compute and storage; DJAI does not host document processing.
Related MCP server: mcp-file-servers
Working MCP tools in v0.1.0
Capability | MCP tool | What the agent can achieve |
AI token counter |
| Measure prompt, document, code, and context size using common tokenizer encodings |
AI context optimizer |
| Remove repeated page furniture, broken prose wrapping, and excess whitespace |
RAG chunk generator |
| Create deterministic token-aware JSONL chunks with configurable overlap |
Prompt/context packager |
| Combine local source files with Markdown or XML boundaries for an AI agent |
CSV to JSON |
| Convert header-based CSV rows into a formatted JSON array |
JSON to CSV |
| Convert an array of flat JSON objects into spreadsheet-friendly CSV |
CSV cleaner |
| Trim fields, remove empty rows, and remove exact duplicates |
QR SVG generator |
| Generate a local SVG QR code from text, URLs, Wi-Fi payloads, or identifiers |
Planned phases cover merge/split/rotate/watermark PDF, PDF text and AI Markdown extraction, local Thai-English OCR, DOCX conversion, PNG/JPG/WebP image conversion and compression, PDF-to-image and image-to-PDF processing, and CSV/XLSX workflows. See ROADMAP.md.
Example agent workflows
“Count the tokens in these requirements and package only the relevant sources for Codex.”
“Clean this CSV, remove exact duplicates, convert it to JSON, and report the row counts.”
“Prepare this extracted document text as 700-token RAG chunks with 100-token overlap.”
“Generate a high-error-correction SVG QR code for this URL.”
Later releases: “OCR these Thai scanned pages, clean the text, and prepare a RAG knowledge base.”
Later releases: “Merge these PDFs, add page numbers, compress the output, and preserve the originals.”
Privacy and security model
The server uses local MCP over stdio; it is not a hosted upload API.
Read root defaults to the current working directory.
Write root defaults to
./djai-output.Existing files are not overwritten unless
--overwriteis explicitly enabled.Real paths and symlinks are checked before file access.
Defaults limit files to 25 MB, packaged batches to 20 files/50 MB, inline text to 100,000 characters, and CSV/JSON to 100,000 rows.
Remote URL fetching and shell commands built from model input are not implemented.
Every successful operation reports the files it created and
modifiedInput: false.
An MCP process still inherits the permissions of the account that starts it. Authorize narrow folders and read the complete security model.
Download, install, and build
Requires Node.js 22.13 or newer and npm.
git clone https://github.com/lovecatisgood-sudo/AI_Agent_MCP_Tool_for_Multi_Docu_PDF_PNG_QR_File_Conversion_Processing_Capability.git
cd AI_Agent_MCP_Tool_for_Multi_Docu_PDF_PNG_QR_File_Conversion_Processing_Capability
npm ci
npm run build
node dist/index.js --versionRun the server from source:
node dist/index.js --profile core \
--allow-read /absolute/path/to/documents \
--allow-write /absolute/path/to/djai-outputAfter the npm package is published, the intended one-command installation is:
npx -y @djai/tools-mcp --profile core \
--allow-read /absolute/path/to/documents \
--allow-write /absolute/path/to/djai-outputConnect an MCP-capable agent
For a source checkout, use the absolute path to the built server:
{
"mcpServers": {
"djai-tools": {
"command": "node",
"args": [
"/absolute/path/to/AI_Agent_MCP_Tool_for_Multi_Docu_PDF_PNG_QR_File_Conversion_Processing_Capability/dist/index.js",
"--profile",
"core",
"--allow-read",
"/absolute/path/to/documents",
"--allow-write",
"/absolute/path/to/djai-output"
]
}
}
}Use absolute paths because desktop agents may start the process from an unexpected directory. Client-specific examples for Claude Desktop, Codex, Cursor, and VS Code are in examples/.
Profiles and exact tool selection
node dist/index.js --profile core
node dist/index.js --profile ai-documents
node dist/index.js --profile data
node dist/index.js --profile qr
node dist/index.js --profile full
# Exact selectors override the profile
node dist/index.js --tools ai.count_tokens,ai.chunk_for_ragcore registers seven broadly useful tools; smaller profiles reduce agent context and selection ambiguity. Read profiles and the complete tool reference.
Original free browser tools
The MCP project grows from the earlier Free PDF, Image, OCR, DOCX, QR, AI and Data Tools. Those applications already provide live, private browser workflows for PDF, image resizing/conversion/compression, Thai-English OCR, documents, QR, AI context/RAG, CSV, JSON, and Excel.
Browser collection | English | ไทย |
All tools | ||
PDF tools | ||
Image tools | ||
Document and OCR | ||
AI token and RAG | ||
CSV/JSON/Excel | ||
QR generator |
About DJAI Academy, Siamese Cat Dev, and Siamese Cat Cafe
DJAI Academy develops practical technology education, software services, AI-agent integrations, and free digital tools for people and businesses.
Siamese Cat Dev is the independent developer and product builder behind this open-source MCP release and the original browser-tool collection.
Siamese Cat Cafe is the connected community business helping support cat adoption and independent creative development. Visitors can also find the cafe on Google.
Stars, contributions, honest feedback, visits to the cafe, and genuine reviews from people who have visited all help sustain the software and community mission.
Follow Siamese Cat Dev
GitHub: @lovecatisgood-sudo
Developer profile: Siamese Cat Dev
Instagram: @djcatdev
Facebook: Siamese Cat Dev
Website: DJAI Academy
Development and contributions
npm run check
npm test
npm run build
npm pack --dry-runUse only synthetic fixtures—never commit personal, proprietary, confidential, or credential-bearing documents. Read CONTRIBUTING.md, SUPPORT.md, SECURITY.md, and the Code of Conduct.
MIT License and attribution
This project is free and open source under the MIT License. You may use, copy, modify, merge, publish, distribute, sublicense, and sell copies, including in commercial and closed-source products, provided the MIT copyright and permission notice is retained in copies or substantial portions.
Visible backlink credit is not required by MIT, but it is warmly appreciated:
Creator: Siamese Cat Dev at DJAI Academy
Original tools: Free PDF, Image, OCR, DOCX, QR, AI and Data Tools
Community business: Siamese Cat Cafe
See ATTRIBUTION.md for copy-ready examples. The MIT License does not grant trademark rights or permission to imply endorsement; see TRADEMARKS.md.
Available Tools
7 toolsdjai_ai_chunk_for_ragChunk Text for RAGA
Split local text into deterministic o200k_base token chunks and write JSONL for a RAG knowledge base. Use after extraction and cleanup. Do not use overlap equal to or larger than chunk_size.
Inputs: text, overlap, chunk_size, input_path, +1 more.
djai_ai_count_tokensCount AI TokensA
Count tokens and text metrics locally. Use before budgeting prompt or RAG context. Accepts inline text or an allowed local UTF-8 file; it never modifies files.
Inputs: text, encoding, input_path.
djai_ai_optimize_contextOptimize AI ContextA
Clean repeated headers, page labels, broken line wraps, and excess whitespace from local text. Use before prompting or chunking extracted document text. Do not use when exact formatting must be preserved.
Inputs: text, input_path, output_path.
djai_ai_package_promptPackage Prompt ContextA
Combine multiple allowed local UTF-8 files into one agent-ready Markdown or XML-delimited context file. Use to preserve source boundaries. Do not use for binary files or more than the configured batch limit.
Inputs: input_paths (required), boundary, output_path, instructions.
djai_data_clean_csvClean CSVA
Trim headers and values, remove empty rows, and remove exact duplicate rows from CSV locally. Use for basic cleanup; do not use when whitespace or duplicate rows are semantically meaningful.
Inputs: input_path (required), output_path.
djai_data_csv_to_jsonConvert CSV to JSONA
Convert a header-based CSV file into a formatted JSON array locally. Use for structured imports and APIs. The input is preserved and output is written only to an allowed directory.
Inputs: input_path (required), output_path.
djai_qr_generateGenerate QR SVGA
Generate a deterministic QR code as a local SVG file. Use for text, URLs, Wi-Fi payloads, or identifiers. It does not fetch or validate remote URLs and never embeds a remote image.
Inputs: content (required), width, margin, dark_color, +3 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose: token counting, text cleanup, RAG chunking, prompt packaging, CSV conversion, CSV cleaning, and QR generation. No two tools overlap in functionality.
All tools follow a consistent prefix (djai_ category) and verb_noun snake_case pattern (e.g., djai_ai_count_tokens, djai_qr_generate), making the surface predictable.
7 tools is well-scoped for a server offering AI text preprocessing, data conversion, and QR generation utilities—not too few, not too many.
The tool set covers the core workflow of text handling (count, clean, chunk, package) and data conversion (CSV), with QR as an extra. Minor gaps like a generic concatenate tool exist, but the surface supports common tasks fully.
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