sheawinkler/ContextLattice
by Various
ContextLattice is the local-first control plane for long-horizon agent memory and coordination.
MCP
sheawinkler/ContextLattice
Added 1 June 2026
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
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
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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Hindsight: Agent Memory That Learns