Kit For AI
Kit for AI provides document conversion, persistent memory, and knowledge-base tooling as a unified platform and API for AI agents and RAG pipelines — converting files and URLs to clean Markdown/JSON, enabling semantic search, citation-backed KB chat, and MCP-native memory integration.
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Quick Overview
Best for: AI Agents
What it does
AI Tools software for decision-makers comparing workflow fit and alternatives.
Best fit
AI Agents
Pricing snapshot
Freemium from $0
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Kit For AI
Kit for AI is a platform and API that converts files and web pages into clean, model-ready Markdown or JSON, provides persistent memory and knowledge bases for AI agents, and exposes those capabilities natively to MCP-compatible agents or via REST. It targets developers, ML engineers, and teams building RAG pipelines or agent workflows by removing the need to assemble and maintain a multi-service stack (vector DB, parser, embedder, reranker) and by providing conversion, embedding, semantic search, citation-backed KB chat, and memory primitives in one product.
The product emphasizes privacy and production readiness (private by default, encrypted at rest, isolated infrastructure, scoped API keys), supports batch processing and scheduled refreshes, and advertises startup-friendly onboarding with a free tier and REST/MCP integration options for immediate use.
The memory layer for AI agents Discussion | Link
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Document conversion
Convert PDF, DOCX, XLSX, PPTX, CSV, HTML, images (OCR), plain text/Markdown and more into clean, chunked Markdown suitable for LLMs and RAG pipelines.
URL & web → Markdown
Fetch web pages (including JS-heavy and gated sites), strip nav/ads/footers, and return main content as clean Markdown with preserved tables and structure.
OCR & image extraction
Extract text from scanned documents and images (PNG/JPG/WebP) via OCR and convert results into searchable documents.
JSON extraction / schema shaping
On Pro, extract structured JSON shaped to your schema so documents map directly into typed fields for invoices, forms, and reports.
Knowledge bases & grounded chat
Create searchable KBs that the agent can query; KB chat returns cited answers with links to source passages and visual graphs of connected docs.
Persistent memory primitives
Remember, recall, and search over memories as MCP tools with versioning, near-duplicate deduplication, and memory usable mid-conversation.
Semantic search with reranking
Hybrid retrieval combining vector embeddings and full-text search, then reranking (in-house relevance scoring, Reciprocal Rank Fusion) to surface best passages.
MCP-native and REST integration
Works as MCP-native tools and via REST API — examples and MCP server configuration provided for quick agent wiring.
YouTube transcript ingestion
Convert YouTube links into transcripts that become searchable documents for KBs and allow cited Q&A over video content.
Batch processing and scheduling
Batch uploads (up to 25 mentioned), scheduled URL refresh to keep sources current, and per-key rate-limited API processing.
Privacy and security
Private by default: isolated infrastructure, encrypted-at-rest storage, hashed API keys, per-key rate limits, and project 'spaces' to isolate data.
Token-efficient retrieval
Targets up to 90% fewer tokens by pulling only relevant passages and returning compact cited results to reduce cost and latency.
Pricing
Freemium: $0 — includes 20 KB chat messages/month, 10 file/page conversions, 5 video transcripts, and 1 knowledge base.
Freemium
$0- Chat with your documents — 20 messages a month
- Turn 10 files or web pages into clean text
- Turn 5 videos into searchable notes
- 1 knowledge base
Pro
Invite only- Chat with your documents — 1,500 messages a month
- Convert 2,000 files or web pages
- Turn 150 videos into searchable notes
- 25 knowledge bases · 25 GB storage
Business
Invite only- Everything in Pro with higher limits
- Chat with documents — 10,000 messages a month
- Convert 20,000 files or web pages
- Turn 1,000 videos into searchable notes
Use Cases
RAG pipelines
Convert document libraries into clean, chunk-ready Markdown or JSON to populate vector stores and support retrieval-augmented generation workflows.
AI agents with persistent memory
Give agents lasting memory and grounded knowledge they can call mid-conversation (remember/recall/search) to maintain user state and preferences.
Invoice, form, and field extraction
Extract typed JSON fields from scanned or digital documents and map them to custom schemas for automation and downstream processing (Pro feature).
Chat with videos and transcripts
Ingest YouTube videos to create searchable transcripts so agents can answer questions and cite specific parts of lectures, talks, or podcasts.
Fine-tuning and dataset creation
Turn structured Markdown or JSON outputs into clean training datasets and fine-tuning material for models.
Batch conversion at scale
Process many files and links in bulk via the API with per-key rate limits and produce consistent, model-ready outputs.
Integrations
MCP (Model Context Protocol)
Native MCP server integration so agents can call memory, conversion, and search tools mid-conversation.
REST API
Full REST API for conversion, memory, and search (examples and endpoints shown on the page).
Claude Code plugin
Plugin marketplace entry and installation example to wire Kit for AI into Claude and other MCP clients.
Multiple LLMs / models
Works with OpenAI, Claude, Gemini, Meta, Mistral, Perplexity, DeepSeek, Cohere, Grok, Qwen and other model providers as shown on the page.
Benefits
Limitations
Frequently Asked Questions
Which file formats are supported?
Can I convert a web page or URL, not just a file?
How is this faster than other tools?
What makes the output good for AI?
Can I extract specific fields as JSON?
Can my AI and my tools connect directly?
Can I process files in bulk?
How is my data handled and retained?
Is my data encrypted?
What happens if I hit my plan limit?
Getting Started
- 1 Step 1: Start a free account on kitforai.com (no credit card required).
- 2 Step 2: Create an API key from the dashboard and note scoped key usage and rate limits.
- 3 Step 3: Install or configure — use the MCP server (example URL https://kitforai.com/api/mcp), install the Claude Code plugin, or call the REST API endpoints shown on the site.
- 4 Step 4: Upload documents, paste URLs or YouTube links, or call the /memory or conversion endpoints to convert and ingest content into knowledge bases.
- 5 Step 5: Point your agent or model at the Kit for AI MCP server or REST API to enable memory, search, and KB-backed chat in your assistant.
Support
docs
Documentation and guides (site lists 'Documentation', 'Guides', 'Playground' and a full API reference).
blog
Product and implementation guides available on the Kit for AI blog.
playground
Playground and examples for testing conversions and integrations.
self-serve onboarding
Start free, create API keys, and self-configure agents via kitforai.com/llm-setup per the site.
API
https://kitforai.com/llm-setup (site references an MCP server URL, API examples, and a full API reference)
Per-minute and per-key rate limits; conversions metered per month by plan (page mentions per-minute rate limits and per-key rate-limiting).
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