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sheawinkler/ContextLattice

by Various

ContextLattice is the local-first control plane for long-horizon agent memory and coordination.

S

MCP

sheawinkler/ContextLattice

Added 1 June 2026

#agent-framework #agent-orchestration #ai-infra #ai-interface #context-engineering #context-management #golang #long-horizon-agents

Overview

ContextLattice is a local-first control plane for long-horizon agent memory and coordination. Built in Go, it provides persistent context and state synchronization for agents across extended tasks without relying on cloud services.

Best for

Best for
Developers building long-running autonomous agents that need persistent local memory and coordination

Use cases

  • Maintaining agent context across multi-step workflows
  • Coordinating memory and state between multiple autonomous agents
  • Running persistent agent loops on local hardware

How to use

Tools exposed

  • git
  • gmake
  • curl
  • jq

Tested with

Codex, Claude Code, Hermes, OpenCode, OMP, Mercury, Pi, Droid

Notes

ContextLattice is a local-first control plane for long-horizon agent memory and coordination. Built in Go, it provides persistent context and state synchronization for agents across extended tasks without relying on cloud services.

109 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

  • Maintaining agent context across multi-step workflows
  • Coordinating memory and state between multiple autonomous agents
  • Running persistent agent loops on local hardware

Pros

  • Local-first design reduces latency and privacy risks
  • Go implementation offers fast, concurrent performance
  • Open source with a permissive license

Cons

  • Relatively new project with 109 stars and a small community
  • Limited documentation beyond the README
  • No built-in integrations with popular AI frameworks

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Local-first design reduces latency and privacy risks
  • Go implementation offers fast, concurrent performance
  • Open source with a permissive license

Cons

  • Relatively new project with 109 stars and a small community
  • Limited documentation beyond the README
  • No built-in integrations with popular AI frameworks
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