Morphik

Morphik is an open-source multimodal retrieval engine that ingests and organizes unstructured data such as videos and PDFs for AI application development.

Morphik is a retrieval engine designed to handle unstructured data, including video and PDF files, using custom research-driven algorithms. It offers a flexible model registry that allows developers to register and mix different AI models based on specific task requirements, such as using smaller models for simpler operations. The platform enables multi-user and folder-based access controls to maintain logical boundaries for projects or user groups. Users can provision isolated applications, each with a unique Morphik URI for per-customer or per-project data separation. Additionally, Morphik features built-in Model Context Protocol (MCP) support to integrate knowledge bases with MCP clients. The core code is source-available.

Morphik at a glance

Best for: Software engineer, Researcher
Pricing: Freemium
Released: November 2024
Category: AI research tool
Website: morphik.ai

Key features

Native Model Context Protocol support
Direct ingestion of unstructured data like video and PDFs
Research-driven retrieval algorithms
Multi-user and folder-based access controls
Flexible model registry for task-specific AI model configuration
Isolated application provisioning with unique URIs
Source-available core codebase

Use it for

Building isolated applications with specific data boundaries
Integrating AI knowledge bases with MCP clients
Retrieving information from diverse unstructured data formats
Managing multiple AI models for different project tasks

Alternatives to Morphik

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Morphic — Self-hostable AI search with cited answers and any model provider
OpenResearch — Run parallel research workflows locally or on remote compute.
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memsearch — It shares continuous context across Claude Code, Codex, and other AI coding agents.
Orama — Runs in browsers, servers, and edge networks with zero dependencies.
MemFree — It combines hybrid web search with AI summarization and page generation.
Jina — It provides reliable reader and search APIs optimized for LLMs and RAG systems.
HippoRAG — Improves multi-hop retrieval and complex sense-making without sacrificing simple task performance.
seekdb — Unifies relational, vector, and text data for production-grade AI agents.
DeepSearcher — Performs evaluation and reasoning based on private enterprise data using various models.
UltraRAG — Build complex RAG workflows using modular MCP components and YAML configuration.

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