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Greplica

Greplica is a persistent, searchable engineering memory for AI coding agents. It helps agents recover repository context, query prior work, and share memory across local or managed repository workflows.

Greplica

Persistent engineering memory for coding agents

Greplica is a persistent, searchable engineering memory for AI coding agents. It is designed to reduce the time agents spend re-learning repository context by exploring the codebase, repository structure, and prior session transcripts, then making that information queryable before the agent starts grepping again.

The project supports two operating modes. Local mode keeps data fully local with no telemetry, while managed mode connects an authorized repository to shared team memory so contributors on different clones and forks can query the same repository memory. The source also notes that Greplica requires Node.js 22-26 and can be installed through an agent-driven setup flow rather than by hand.

Core capabilities

Persistent repository memory

Explores repository structure, code, and session transcripts so the agent can query maintained memory before re-grepping the project.

Local and managed operation modes

Supports local mode for fully local operation and managed mode for shared repository memory across contributors.

Searchable context retrieval

Lets agents ask for repository context before acting, including example queries such as what to know before changing a subsystem.

Graph-based memory inspection

Provides a browser graph view to inspect current memory and generated relationships visually.

GitHub-based access control

Uses GitHub authentication and repository invitations to connect users to managed memory and shared access.

Managed memory reconciliation

Includes a managed reconciliation workflow that checks exact default-branch code and produces evidence-bound audits for memory updates.

Practical workflows

  • Context recovery before implementation

    Use Greplica when an agent is starting a complex task and needs to recover repository facts, prior decisions, or subsystem context before making changes.

  • Shared team memory across clones and forks

    Use managed mode when several contributors are working from separate clones or forks but need the same shared repository memory for coordinated work.

  • Visual review of stored memory

    Use the graph view to inspect the current memory graph in a browser and understand how code, sessions, and related context are connected.

  • Memory reconciliation for managed repositories

    Use the reconciliation workflow in managed repositories to compare memory updates against exact default-branch code and produce evidence-backed audits.

Pros and Cons

Pros

  • Builds persistent memory from repository structure, code, and session transcripts instead of relying on each new session to rediscover context.
  • Supports fully local operation with no telemetry in local mode.
  • Enables shared team memory in managed mode for contributors working from different clones or forks.
  • Provides queryable context and graph views to inspect stored memory before making changes.
  • Documents a managed workflow for reconciling memory against exact default-branch code.

Cons

  • The documentation is partial in the available source, so some setup and workflow details are not fully specified here.
  • Managed mode depends on access to a managed Greplica server and administrator-granted repository or organization access.
  • The source does not provide pricing for Greplica itself.

FAQ

How do you install Greplica?

Greplica is installed into a repository and can be used in local mode or managed mode. The source says most users should start by pasting the install prompt into their coding agent from inside the repo they want Greplica to remember.

Does Greplica run locally or require a hosted service?

Local mode stays fully local and uses SQLite for repository binding, role cache, hook policy, and runtime session metadata. The source says it has no telemetry in local mode.

What is managed mode used for?

Managed mode lets contributors on different clones and forks query the same repository memory. It requires Greplica 0.2.0 or later, access to a managed Greplica server, and a GitHub user who has been invited by an administrator.

What are the setup requirements?

The README says Greplica requires Node.js 22-26. The package metadata lists Node 22.x through under 27.x as the supported engine range.

Which agents or platforms does Greplica support?

The source mentions a browser graph view command, query examples for repository context, and managed-memory invite links, but it does not provide a complete list of supported agent platforms beyond examples that include Codex.

Quick Facts

Category
Developer Tool
Source domain
github.com
Primary users
AI coding agents and developers using them
Deployment modes
Local, managed
Runtime requirement
Node.js 22-26
License
MIT
Greplica - AI Tool, Features, Use Cases & Alternatives | UStack