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AI memory 2026 Rank: #1189

Knowledge Plane ✓

Shared memory for AI agents and teams.

Source rating 5.0 (2) 753 views 11 saves 2 comments Freemium
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Enterprise AI Graph Database Knowledge Base AI memory
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Free + from $19/mo

Verdict

A quick read before you dig into the full page.

Best if
Shared memory for AI agents and teams
Skip if
Complex Graph and Vector Model
Pick this when
Consolidates team's code, documentation, chats

Considering Alma by Olivares.AI instead? Compare side by side

Overview

Knowledge Plane is a shared memory layer designed to streamline workflows and facilitate communication by allowing teams to work in their preferred AI toolslike Cursor, Claude, and otherswithout creating new silos.

It aims to consolidate a team's code, docs, and chats into a comprehensive and up-to-date source of truth that is auditable across existing tools. The system automatically extracts and cleans data from ingested documents or synced GitHub repos.

Knowledge Plane combines Graph capabilities that model relationships with Vector Embeddings for understanding semantics. It is designed to plug into AI agents like Claude and Cursor through the Model Context Protocol (MCP), with no custom integrations needed.

The platform auto-ingests existing documentation and codes to build knowledge cards and also offers self-hosting options for those who prefer to keep proprietary context within their infrastructure.

Knowledge Plane isnt a simple vector store but combines graph memory with vector embeddings to allow AI agents to reason about dependencies, ownership, and timelines.

Additionally, it features workspace isolation, full audit logs, and scoped API keys for security concerns.

  • Knowledge Cards — Atomic Facts Extracted From Docs, Not Raw File Storage. Higher Accuracy Under Tight Context Windows • Skills — Scheduled Autonomous Jobs That Detect Drift And Update Facts Automatically (hourly/daily). This Is A Real Differentiator, Most Tools Don't Have This • Graph Memory With Typed Edges (depends_on, Decided_by, Owned_by) — Agents Can Traverse Chains Of Decisions Like A Senior Team Member Would • Hybrid Retrieval: Graph Traversal + Vector Search Combined • Auto-ingestion From Google Drive, Github Repos, Pdfs, Wikis, Tickets
Knowledge Plane website

Access & connections

Where you can use Knowledge Plane, and what it plugs into.

Platforms

Web

Integrations

Google Drive GitHub MCP

API

Public API available

Browse other tools with an API

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Code
  • Tabular
  • Image
  • Text
  • Video
  • Audio

Output

  • API
  • Text

Highlights

  • Agents
  • API
  • MCP
  • Waitlist

Supported features

  • Agents
  • API
  • MCP

Pros & cons

Pros

  • Consolidates team's code, documentation, chats
  • Prevents context exhaustion
  • Exceptional long-term memory
  • Ability to auto-ingest
  • Auto extraction from documents, codebases
  • Knowledge cards creation
  • Combines Graph and Vector embeddings
  • Understands dependencies beyond keywords
Show 35 more
  • Built on Model Context Protocol
  • Query with standard MCP protocol
  • No need for custom integrations
  • Offers data sovereignty
  • Self-hosted option available
  • Enhanced governance with audit logs
  • Provided workspace isolation
  • Scoped API keys for security
  • Trails for every query, update
  • Automated Github data extraction, cleaning
  • Integrates across platforms
  • Workflow management system
  • Facilitates inter-agent communication
  • Offers semantic understanding
  • Structured intelligence provision
  • Prevents fragmentation in team memory
  • Enables understanding of relationships and semantics
  • Service-dependency comprehension
  • Turns files to knowledge cards
  • Autonomous update of knowledge base
  • Interprets ownership, timelines in codebases
  • extracts, cleans data from documents
  • Transforms amnesic chatbots to knowledgeable agents
  • Automatic data from document ingestion
  • Combines vector store with Graph memory
  • Relationship modeling with semantic search
  • Combines graph memory with vector embeddings
  • Features workspace isolation
  • Full audit logs available
  • Automatically scans docs, codebases
  • Understands team dynamics
  • Structured hybrid engine for modeling relationships
  • Self-organizing structure
  • Provides team-wide synchronized knowledge
  • Persistent shared memory layer

Cons

  • Complex Graph and Vector Model
  • Dependent on Model Context Protocol
  • No clear pricing information
  • Requires regular source updating
  • Potential learning curve
  • Risk of information overload
  • Limited Workspace Isolation
  • Self-hosting may be complex
Show 1 more
  • Limited early access availability

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Releases 1

Initial release February 13, 2026 Current
Initial release of Knowledge Plane.

Imported reviews 1

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Vitaliy Filipov Feb 12, 2026 v@ initial release

I'm in early beta and I'm managing to orchestrate my 3 openclaw agents with my 2 claude code sessions. It's cool, maybe this is the future.

FAQ 12

What is Knowledge Plane?
Knowledge Plane is an AI-based shared memory tool designed for engineering teams. It consolidates a team's code, documentation, and chats into a unified, updated source of information to ensure consistent quality from AI tools. It bridges the infrastructural gap of fragmented memory among different AI tools, transforming amnesic chatbots into agents with long-term memory.
How does Knowledge Plane work?
The functionality of Knowledge Plane is based on automatically scanning documents and codes, extracting raw facts, cleaning data, and creating knowledge cards. It combines Graph capabilities to understand dependencies with vector embeddings to locate keywords. AI agents connect to Knowledge Plane via the Model Context Protocol (MCP), eliminating the need for custom integrations. It also features workspace isolation, scoped API keys, and maintains audit trails for all queries and updates for added security.
What is the purpose of Knowledge Plane's auto-ingestion feature?
The purpose of Knowledge Plane's auto-ingestion feature is to automatically scan documents and codebases, extract raw facts and clean data, and create knowledge cards. This functionality enables an efficient and automatic consolidation and organization of information, obviating manual effort.
What are the benefits of Knowledge Plane's Graph capabilities and vector embeddings?
Knowledge Plane's Graph capabilities and vector embeddings facilitate a profound understanding of dependencies, not just keywords. Graph capabilities model relationships between elements, while vector embeddings assist with semantic understanding. Thereby, it enables AI agents to reason about dependencies, ownership, and timelines instead of simply keyword matching.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is a standard protocol that AI agents like Claude and Cursor can leverage to query Knowledge Plane. It is designed to eliminate the need for custom integrations.
How does Knowledge Plane use the MCP?
Knowledge Plane uses the Model Context Protocol (MCP) to allow compatible AI agents like Claude and Cursor to query the plane directly. This simplifies and streamlines its integration into existing AI ecosystems without the need for custom implementations.
How does Knowledge Plane ensure data sovereignty?
To ensure data sovereignty, Knowledge Plane provides a self-hosted option, enabling organizations to keep proprietary information within their infrastructure. The tool extracts structured facts and relationships but does not store raw copies of files, ensuring that original documents remain in place while providing a structured and governed extraction of knowledge.
What does the self-hosted option in Knowledge Plane entail?
The self-hosted option in Knowledge Plane allows organizations to keep their proprietary information within their infrastructure by deploying Knowledge Plane within their own enterprise environment. This preserves data sovereignty as the data does not leave the safe confines of their network and remains fully under their control.
How does Knowledge Plane handle audit logs?
Knowledge Plane handles audit logs by logging every query and update. It tracks who made the request, when it was made, and backs every fact to its source, providing a comprehensive audit trail. This enhances governance and ensures transparency and accountability within the system.
What are knowledge cards in Knowledge Plane and how are they created?
In Knowledge Plane, knowledge cards are created by the system's automatic ingestion and structuring of data. The system scans documents and codebases, extracts raw facts, cleans the data, and consolidates the information into high-density knowledge cards. These knowledge cards encapsulate atomic facts and a large view of context within a structured format, facilitating better comprehension and utilization for AI agents.
How does Knowledge Plane assist in workflow management?
Knowledge Plane assists in workflow management by acting as a unified memory tool for the entire team. It consolidates all code, documentation, and chat data into a single up-to-date and auditable source of truth across various tools. This ensures a more streamlined workflow as teams don't have to switch between tools or lose context when transitioning.
What AI tools can Knowledge Plane integrate with?
Knowledge Plane can seamlessly integrate with AI tools like Cursor and Claude via the Model Context Protocol (MCP). This allows an undisturbed workflow in teams' preferred AI tools without the need to create new silos or perform custom integrations.
Knowledge Plane Free + from $19/mo
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