Your coding assistant works in sessions.

Your codebase lives forever.

Coding assistants have no memory of the last request, no knowledge of why a particular architectural decision was made, and no shared context with the coding agent running in the next developer’s IDE.
Meko gives coding assistants a persistent, shared data layer. This means that institutional knowledge compounds across every session, every developer, and every agent. Coding agents understand project architecture, coding standards, and team conventions, letting application teams maintain consistency across development.

THE PROBLEM

Modern coding agents are stateless by design.

AI coding assistants may now be indispensable, but they all share the same structural limitation: they only know what’s in the current context window. When the session ends, that context disappears. When another developer opens the same assistant, it starts fresh, and if an agent encounters a pattern it “learned” last week, it can not recall it. This isn’t a model problem, it’s a data infrastructure problem that compounds as teams grow and agents multiply.

Context rot

One agent’s outdated assumption becomes the starting point for the next. Errors amplify across sessions and across developers.

Duplicate inference

Every agent independently re-derives the same architectural patterns, coding conventions, and domain context, burning tokens each time.

No shared learning

When your best engineer’s coding session produces something valuable, that knowledge vanishes the moment the window closes.

THE SOLUTION

Meko: the memory and knowledge layer for coding agents.

Connect your coding assistant to a Meko datapack through a single MCP endpoint. From that point, every session can read shared knowledge, record new learnings, and build on a shared foundation created by every agent in the system.

$ meko datapack create –agent_name research-agent

One simple command and a single endpoint allows every coding agent in your organization to share memory, knowledge, and context.

HOW IT WORKS

A datapack is your codebase’s institutional memory.

A Meko datapack stores everything a coding agent needs to be genuinely useful across sessions:

Per-agent memory keeps each developer’s agent aware of their personal preferences, recent decisions, and ongoing work context, privately, without leaking into shared space.
Shared knowledge captures architectural patterns, coding conventions, domain context, and past decisions that every agent in the organization can access and build on.
Conversation history retains the full reasoning behind past interactions, automatically tiering older content to object storage to keep costs predictable.
Full auditability gives you a traceable record of what agents learned, when, and from which context, so you can understand how knowledge flows through your engineering organization.

CAPABILITIES

Built for how coding agents actually work.

Single MCP Endpoint

Connect any coding assistant that supports MCP. One endpoint provides the agent with access to memory, knowledge, SQL, vector search, and graph queries, without changing your tool or workflow.

Collective
Memory

When one developer’s session produces an architectural insight, it’s immediately available to every other agent in the system. Knowledge that was locked in one context window becomes organizational infrastructure.

Knowledge from Your Codebase

Point Meko at your repos, docs, ADRs, and wikis. It processes them automatically, building a continuously updated knowledge layer your agents can query at inference time.

Context-Aware Retrieval

Meko surfaces the right knowledge at the right moment. Agents don’t have to ask, and you don’t have to stuff your context window with disparate documentation you hope might be relevant.

Auto-Tiered Storage

Conversation history and older memory are automatically tiered to object storage and warmed back up on demand. You get enterprise-grade persistence without enterprise-grade infrastructure costs.

Full
Observability

Every memory read, knowledge retrieval, and data operation is traceable. View exactly what your agents learned, what they accessed, and what shaped their suggestions.

COMPATIBILITY

Works with the tools your team already uses.

Meko connects to any coding assistant that supports MCP, including:

Claude

Cursor

GitHub Copilot

Codex

Support for additional coding assistants is expanding continuously. If your tool supports MCP, it works with Meko.

WHO IT’S FOR

For engineering teams who want agents that get smarter over time.

Platform & infrastructure teams

Standardizing on AI tooling across a large engineering organization and need consistent context, conventions, and knowledge shared across every developer’s agent.

Enterprises with complex, long-lived codebases

Where domain knowledge is deep, turnover is real, and every new developer or agent starting from scratch is an expensive problem.

Teams running multi-agent workflows

Multiple coding agents collaborate on the same codebase and need shared state to avoid conflicting decisions and duplicated reasoning.

DEPLOYMENT

A managed service, built for production.

Meko is available today as a fully managed service. You bring the agents, and Yugabyte handles the infrastructure, scaling, reliability, and data tiering. Open source deployment is on the longer-term roadmap.

WHAT CHANGES

Before and after Meko.

	Without Meko	With Meko
Session memory	Lost on close	Persisted per agent
Shared knowledge	None	Compounds across the team
Codebase context	Re-derived every session	Queried at inference time
Knowledge propagation	Manual (if at all)	Automatic
Agent observability	Partial	Full chain-of-thought
Infrastructure	DIY stitching	Single MCP endpoint

Provide coding agents with memories worth keeping.

Your tools are already good, they are just missing context that persists. Meko closes that gap.

Built on YugabyteDB, distributed PostgreSQL powering industry-leading mission-critical applications.