Chat Recall

What is Chat Recall?

Chat-Recall is a centralized search engine, secret-auditing utility, and persistent cross-tool memory layer built for developers and engineering teams who code with multiple AI assistants. Initialized via a single command (npx chat-recall init), it scans local disk storage to index conversations, task lists, and architectural plans created across different AI coding environments, transforming fragmented chat logs into a unified, searchable developer knowledge base.

Designed around the concept of turning forgotten AI coding sessions into a searchable second brain and shared agent memory, chat-recall bridges isolated assistant silos. Instead of losing debugging breakthroughs, setup instructions, and code decisions inside closed tool histories, chat-recall aggregates conversations across major AI coding tools, strips out leaked credentials on your local machine before any sync occurs, and exposes past findings back to active agents through standard Model Context Protocol (MCP) tools.

• Platform Role: AI Coding Chat History Search, Secret Leak Detector & Cross-Assistant MCP Memory Server
• Supported Ecosystems: Multi-assistant support indexing conversations across five major AI coding tools, CLI agents, and developer environments
• Installation & Protocol: Node CLI (npx chat-recall init), Model Context Protocol (MCP) server integration, and open self-hosting

Use Cases:

• Searching through months of past AI coding conversations, technical decisions, and bug-fix recipes across multiple tools in one place
• Detecting and auditing leaked API tokens, database passwords, and secret keys across chat logs with on-device redaction
• Connecting active AI agents (e.g., in Claude or Cursor) to past project findings via MCP tools so they recall historical context automatically
• Synchronizing AI tool configurations, custom rules, and installed skills across multiple development laptops without manual copying
• Self-hosting a complete, private AI chat search and memory server for individual or corporate compliance requirements

Technology:

• Local on-device parsing engine that extracts raw chat transcripts and plans stored on local disk by AI coding utilities
• Client-side credential masking pipeline that redacts API keys (e.g., OpenAI, Anthropic, AWS tokens) before network transmission
• Model Context Protocol (MCP) server interface allowing AI assistants to query past transcripts and tasks programmatically
• Self-hostable architecture enabling complete offline deployment where chat data never leaves your infrastructure

Target Users:

• Software engineers and vibe coders switching between multiple AI coding assistants, IDEs, and CLI tools
• Engineering leads auditing AI chat logs for accidental API secret leaks and security vulnerabilities
• Developers setting up new workstations who want instant access to previous AI troubleshooting histories
• Privacy-conscious teams requiring local or self-hosted indexing for proprietary code discussions

Acquisition: Developer CLI tool and hosted platform 

What are the key features of chat-recall?

chat-recall's key platform features are

• One-Command Installation: Run npx chat-recall init to index existing transcripts, detect installed AI tools, and register MCP servers automatically.
• Universal Chat Search: Fast, full-text search across all your past AI conversations, debugging sessions, and architectural plans.
• Client-Side Secret Masking: Automatically identifies and redacts API keys and credentials on your machine before data leaves your computer.
• Leaked Key Security Dashboard: Audits leaked keys by rule, checks if exposed credentials are still active, and shows affected conversations.
• MCP Server Integration: Exposes memory and past project findings directly to AI coding agents via standard Model Context Protocol tools.
• Cross-Machine Setup Sync: Keeps rules, skills, and chat histories synchronized across multiple development machines.
• Full Self-Hosting Option: Run the complete platform on your own hardware for zero cost and maximum data privacy.

How much does chat-recall cost?

chat-recall offers a fully featured free tier for individual developers alongside self-hosting options, with hosted Solo, Team, and Enterprise plans for centralized organizational sync.

Pricing Plans:

• Self-Hosted ($0): 100% free forever for one person. Access all core features, local parsing, MCP server tools, and search on your own infrastructure with zero fees.
• Free Cloud Tier ($0): Free individual starter access on the hosted cloud service to test multi-tool indexing and basic search.
• Solo Cloud: Paid subscription for individual developers wanting managed cloud backup, multi-device sync, and unmetered transcript search without self-hosting overhead.
• Team & Enterprise: Organizational plans providing multi-seat licenses, team-wide leaked secret alerts, centralized project knowledge sharing, and enterprise SSO.

Disclaimer: Transcripts live primarily on your local disk; running `chat-recall sync --full` reconciles data with the server at any time. Review chatrecall.dev/pricing for active plan terms.

Who should use chat-recall?

chat-recall is designed for software developers and technical security teams, including

• Multi-Tool AI Developers: Searching for past code snippets without remembering whether they were generated in Cursor, Claude, or a terminal agent.
• Security-Conscious Engineers: Preventing exposed production API keys and database credentials from lingering in unmonitored AI chat caches.
• Agentic Workflow Builders: Giving active AI coding agents access to past project context and architectural decisions via MCP.
• DevOps & Platform Leads: Standardizing developer agent rules and configuration across distributed engineering teams.

What are the best alternatives to chat-recall?

Some of the strongest chat-recall alternatives include

• Mem0 
• Zengram 
• GitGuardian 
• TruffleHog 
• ChatHop 
• TypingMind 

What are the pros and cons of chat-recall?

What are the pros of chat-recall?

• Eliminates fragmented chat silos across multiple AI coding assistants with one command
• Crucial security layer: strips API keys and credentials locally on your own machine before transmission
• Standard Model Context Protocol (MCP) server integration lets current AI agents read past solutions
• 100% free self-hosting option provides full features for solo developers without vendor lock-in
• Automates workstation migration by making your entire AI history available on new machines

What are the cons of chat recall?

• Tailored specifically for AI coding assistants and developers rather than general-purpose web chatbots
• Requires command-line setup (Node.js/npx) to initialize and manage local transcript indexing
• Custom internal proprietary secret patterns require manual pattern configuration to detect

Why should you choose chat-recall?

As software engineers adopt multiple AI coding assistants, they scatter valuable architectural discussions, debugging breakthroughs, and task lists across isolated databases and hidden local folders. Even worse, developers frequently paste production API keys directly into prompts, creating invisible security liabilities. Chat-recall addresses both problems at once. By indexing your entire AI coding history, redacting secrets locally before sync, and serving past solutions back to active coding assistants via MCP, chat-recall turns disconnected chat logs into a secure, searchable asset for your engineering workflow.

• Search all past AI coding sessions, decisions, and transcripts in a single location
• Safeguard sensitive credentials with automatic, client-side secret detection and redaction
• Empower active AI agents to recall previous project context using standard MCP tools
• Run it completely free on your own infrastructure with open self-hosting

How does chat-recall compare to competitors?

While GitGuardian and TruffleHog focus purely on scanning code repositories for leaked secrets, and Mem0 functions as a general agent memory API, chat-recall uniquely unifies local AI coding transcript search, secret auditing, and MCP memory into a single developer tool.

How do we rate chat-recall?

What is our review and verdict on chat-recall?

ChatRecall tackles two of the biggest blind spots in AI-assisted software engineering: conversational memory loss and secret sprawl. By transforming unindexed chat transcripts into a unified, searchable knowledge base with local client-side redaction, it restores visibility and control over developer workflows. With native Model Context Protocol (MCP) support that lets current agents read past solutions, alongside an open, full-featured self-hosting model, chat-recall is an essential tool for any engineer building software with AI assistants.

Conclusion

ChatRecall solves the problem of lost conversations by turning chat history into a searchable, structured knowledge base. Instead of scrolling endlessly to find past information, users can quickly retrieve key insights and context with AI. This makes it especially useful for heavy chat users and teams managing ongoing discussions. Overall, ChatRecall improves organization, saves time, and helps users get more value from their conversations by making information easy to access and reuse.