Meredith Labs

Modern AI coding agents with native RAG,
Agent Client Protocol, and intelligent context management.

Built for agent-scale coding

Meredith is an AI coding agent designed for real-world software engineering. It combines retrieval-augmented generation, smart context windows, and a plugin architecture that adapts to your workflow.

RAG-native

Built-in codebase indexing, symbol resolution, and semantic search keep your entire project in reach.

ACP ready

Agent Client Protocol support for seamless editor integration - VS Code, JetBrains, and beyond.

Context-aware

Intelligent context compression, budget tracking, and tier degradation keep the agent focused.

Intake · Transform · Deliver

Inspired by the Meredith Effect's thermodynamic flow - cool analysis, deliberate transformation, and focused execution.

Analyze

Reads your codebase, resolves dependencies, and builds a semantic index of every symbol and structure.

Plan

Decomposes tasks into ordered subtasks using flat or tree-of-thought strategies, then executes with verification.

Deliver

Applies changes, runs diagnostics, and loops until the task is complete - with full traceability.

Everything you need, nothing you don't

LLM

Any model

OpenAI, Claude, local Ollama, or MLX on Apple Silicon - swap providers without changing your workflow.

Tools

File & code tools

Read, write, edit, search, and glob files. Symbol-aware search across Python, TS, Rust, Go, and more.

Web

Live research

Fetch documentation, search the web, and incorporate real-time information into the agent loop.

Memory

Cross-session memory

Persistent SQLite store that saves observations across sessions, filtered for security.

Recovery

Self-healing

Loop detection, plan revision, and tier degradation keep the agent productive when things go wrong.

Audit

Verifiable output

Every step is verified - edit sanity, diagnostics pass/fail, read efficiency - before the agent moves on.