
CodeLedger solves the cold start problem for AI coding sessions by building persistent, deterministic context selection into your repo. It exposes three MCP tools: query_ledger to search verified patterns before writing code, get_active_context to pull the minimal file bundle for your current task, and record_interaction to capture outcomes that compound into institutional memory. Context persists across agents and sessions, so successful patterns from one task automatically inform the next. Works locally with no cloud dependency. The MCP server runs via stdio transport and requires Team or Enterprise tier, though the core context selection and CLI work in the free Individual tier.
Give AI coding agents the right repo context before they start - then verify what changed.
CodeLedger is local-first context control for AI coding agents. It scans a repository, selects a bounded task-relevant set of files, and writes an evidence-backed context bundle before the agent begins work.
Works with Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, and other CLI or MCP-compatible coding agents.
npm install -g @codeledger/cli
cd your-project
codeledger ready --task "Fix null handling in user service"
CodeLedger initializes the repo if needed, refreshes the index, and creates the
task-specific bundle at .codeledger/active-bundle.md. Your agent reads that
artifact first so it starts with the files most relevant to the task.
Runtime analysis is local by default. Installing or updating may fetch packages or release artifacts from npm and GitHub Releases; CodeLedger runtime analysis does not send your source code through CodeLedger telemetry by default.
Example result from a mid-sized Node.js service. Results vary by repository, task, agent, and scenario.
| Metric | Without CodeLedger | With CodeLedger | Change |
|---|---|---|---|
| Tests Passed | 78% | 94% | +16% |
| Iterations | 4 | 2 | -50% |
| Files Changed | 17 | 9 | -47% |
| Time to Finish | 6m 12s | 3m 40s | -41% |
| Token Usage | 28k | 18k | -36% |
Do not take the benchmark on faith - measure CodeLedger on your own repo:
codeledger compare \
--scenario .codeledger/harness/scenarios/auth-rate-limit.json \
--guided
If CodeLedger improves your coding-agent workflow, star the repo to follow releases and help other developers discover it.
.codeledger/active-bundle.md for your coding agent.Same task plus same repo state produces the same file ranking behavior.
For the full command surface, see the CLI Reference.
Claude Code can use CodeLedger hooks after codeledger ready initializes the
repo. Cursor, Codex, GitHub Copilot, Gemini CLI, Aider, Windsurf, and other
agents can read CLAUDE.md plus .codeledger/active-bundle.md, or use the
repo-local wrappers when available.
CodeLedger also includes an MCP server for supported tiers:
codeledger mcp start
codeledger mcp status
See MCP Server and Feature Tiers for setup and tier details.
SHA256SUMS and release-evidence artifacts.codeledger doctor checks the local install, hooks, config, index, and ledger
health.LICENSE-CORE.npm install -g @codeledger/cli
codeledger --version
Or use the release zip:
install.sh.The installer uses the bundled package from the zip, so the installed wrapper version matches the release. The wrapper then fetches the matching hardened binary from the GitHub release unless your environment already provides it.
cd your-project
codeledger ready
codeledger ready --task "Fix null handling in user service"
Inside an initialized repo, you can also use:
codeledger activate --task "Fix null handling in user service"
codeledger doctor
Browser, cloud, and sandboxed environments can use the repo-local runtime
deployed under .codeledger/bin/ after initialization or vendoring.
CodeLedger has an open public surface and a protected hardened runtime:
PUBLIC: CLI wrapper, types, repo scanner, harness, reports, docs, hooks
PROTECTED: Scoring engine, selection algorithm, confidence internals
Use codeledger about, codeledger doctor, and command-specific --explain
output to inspect behavior and evidence without exposing protected
implementation internals.
GitHub may classify the combined licensing structure as "Other" because the repo includes both MIT-covered public files and separately licensed protected runtime terms. Changing the license files should be a human legal decision.
CodeLedger applies Intelligent Context AI's context-control architecture to software engineering. For enterprise-wide governed context across applications and agents, see ContextECF.
CodeLedger is produced by Intelligent Context AI, Inc. See codeledger.dev.