Project continuity infrastructure. Detects context drift and routes token-budgeted AI briefings.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Context Fabric.
cf_captureManual context capture outside of a git commit
cf_driftStandalone drift check β returns severity and stale file count
cf_queryFull context briefing for the current task
cf_healthReport database, capture, hook, and search index health
cf_log_decisionPersist an architecture decision across sessions
Current stable release: v1.2.2. See CHANGELOG.md for the release notes.
Context Fabric is configured for official inclusion in the Model Context Protocol (MCP) Registry.
io.github.VIKAS9793/context-fabricThe context synchronization layer for AI coding agents. Ensure project continuity, eliminate agent memory drift, and manage token budgets automatically across any coding session.
Context Fabric is an MCP server that automatically captures project state on every git commit, detects when stored context has drifted from codebase reality, and delivers structured, token-budgeted briefings to AI agents β without requiring any developer action.
Developers using AI coding agents manually construct and maintain documentation systems, session handoff rituals, and context workflows to compensate for the absence of native project continuity tooling. These workarounds share one property: they go stale after commits, and nothing detects it.
The problem is not that AI forgets. The problem is context drift β stored context becomes incorrect after code changes, and AI agents proceed with that incorrect context confidently.
Context Fabric is the infrastructure layer that solves it at the root.
Context Fabric is powered by CADRE, a five-engine internal architecture. Every engine solves a specific, documented failure mode observed in real developer workflows.
What CADRE is. CADRE is the automated replacement for every manual context management system developers currently build themselves. It sits between the git event stream and the AI agent, deciding what context to capture, when it has drifted, which parts are relevant to the active query, what they cost in tokens, and how to deliver them structured and reliably.
Who CADRE is for. Developers building multi-session AI-assisted software projects who currently spend time on any of the following: updating markdown files after commits, creating session-end summaries, maintaining CLAUDE.md or AGENTS.md files, building RAG pipelines for project context, or manually deciding which documentation to load before each task.
E1 β WATCHER
Installs a git post-commit hook on context-fabric init. Fires automatically on every commit. Reads committed Git blobs instead of the mutable working tree, computes SHA256 fingerprints, extracts exported symbols, calculates token estimates, and upserts everything into the local SQLite store. The developer does nothing after setup.
Replaces: markdown-per-commit workflows, 5-step session rituals, and AI interview workflows used to extract structured project knowledge before sessions.
E2 β ANCHOR
On every cf_query call, compares stored SHA256 hashes against the current state of every tracked file. Returns a DriftReport with a 0β100 drift score and severity classification: LOW (under 10%), MED (10β30%), HIGH (over 30%). Stale files are identified by path and hash delta.
Replaces: manual documentation alignment reviews and the undetected staleness in AGENTS.md that ETH Zurich research (arXiv:2602.11988) demonstrated degrades AI coding performance.
E3 β ROUTER
Runs SQLite FTS5 BM25 against the stored component index using the query text from cf_query. Returns components ranked by relevance. Path matches are weighted 2x over export symbol matches, because a file path carries structural meaning about the codebase organisation. Falls back to recency sort when the query produces zero MATCH results.
Replaces: manual selection of which documentation to include per task, and the modular context selection problem that emerges when projects decompose knowledge across many files.
E4 β GOVERNOR
Applies a configurable token budget ceiling to the E3 ranked output using greedy selection on the relevance-ordered list. Default: 8% of the model context window, leaving 92% for conversation and code. Oversize components are skipped so the remaining budget can still be used by later-ranked matches. Token estimates pre-calculated by E1 mean zero additional file reads at budget selection time.
Replaces: manual token management, and the pattern of keeping sessions alive indefinitely to avoid the cost of context restoration on restart.
E5 β WEAVER
Composes a structured markdown briefing from E3 and E4 output. Sections: Project State, Architecture, Architecture Decisions, Budget Summary. When E2 severity is MED or HIGH, a Drift Warning section is prepended before all other content, so the AI is informed of context reliability before reading it.
Replaces: static AGENTS.md briefings that never update, and the manual briefing preparation that developers perform at every session start.
Initialises the SQLite store, installs the git post-commit hook, stages the stable local runtime under .context-fabric/runtime, and runs an initial capture. Connect the MCP server to your tool and context delivery is active from the next commit.
Initialise your project: Navigate to any git-managed repository and run:
Configure your AI Environment (Cursor/VS Code/Windsurf): Add the following to your MCP configuration file.
Windows Users (Crucial):
Mac / Linux Users:
Use the health commands when validating a local install or recovering from a broken hook/runtime state.
doctor reports schema version, search index version, DB integrity, degraded mode, pending and failed captures, plus hook runtime readiness. doctor --repair refreshes the local runtime bundle, reinstalls the stable hook wrapper, validates .gitignore, and rebuilds the search index when the database is healthy.
spawn npx ENOENT ErrorsThis usually means npx is not in the system's inheritance path for the IDE.
node and the context-fabric binary.where node (Windows) or which node (Mac/Linux) to find your path.If you run VS Code on Windows but your code is in WSL, you must run init inside the WSL terminal and use the WSL-absolute path to node in your config.
On Windows, spaces in your project path (e.g., C:\My Projects\app) can break the npx spawn. If the server fails, consider moving your project to a path without spaces.
If something breaks, please run:
npx context-fabric diag remains available as a compatibility alias.
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