chat-recall vs Jackalope: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of chat-recall and Jackalope — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
chat-recall
chat-recall
Makes every conversation your team has had with AI coding assistants searchable, and flags secrets leaked into those chats.
Key features
- Unified Conversation Search: Full-text search across the chats, plans, task lists and notes written by five supported AI coding tools, searchable the moment they arrive.
- Local Secret Redaction: Passwords and API keys are stripped on your own computer before anything is uploaded; only the last few characters are ever received.
- Leaked Key Reporting: Shows every key found, whether it is still live, and how many conversations it appeared in, with support for custom in-house key formats you register.
- MCP Server and Recall Tools: Exposes the history to your assistants through an MCP server so they can query past work directly rather than starting cold.
- Ranked Action Plan: Derives code findings and a prioritized list of what to fix next, written out as CODE_TASKS.md.
- Self-Closing Bug Tasks: Each detected bug becomes a task with a sketched fix, and closes itself once the problem is actually gone.
- Config Distribution: Skills and MCP configuration follow you to every machine and to whichever assistant you pick up next, with a per-machine view of what is missing.
- Per-Project Rules: Mark a project as a prototype or a live product once, and every assistant that opens it plays by the matching rules.
Best for
- Credential Incident Response: Find which keys were pasted into assistant conversations, whether they are still valid, and where they spread.
- Recovering Past Decisions: Search months of AI conversations to recover a plan or rationale instead of asking the same question again.
- Onboarding a New Machine: Sign in on a new laptop and get the full conversation history and every accumulated skill without copying files by hand.
- Switching Assistants: Try a different AI coding tool without losing the add-ons and context built up in the previous one.
- Team Knowledge Sharing: Share project history selectively with teammates and assign follow-up work from a shared task board.
- Security Review Before Shipping: Run the secret monitor and code findings over accumulated history as a pre-release check.
Jackalope
Jackalope Digital LLC
A desktop workspace for running Codex, Claude Code, Grok, OpenCode, Kimi Code and Antigravity in parallel Git worktrees.
Key features
- Parallel Tasks in Git Worktrees: Every task runs in its own worktree so multiple agents work simultaneously without colliding, with dependencies set when one change needs another.
- Six Supported Agents: Assign Codex, Claude Code, Grok, OpenCode, Kimi Code or Antigravity per task, using each agent's own installed CLI and permission rules.
- Interactive Codebase Map: Browse resolved file dependencies to trace the reach of a change and choose what to inspect next during review.
- Carried-Forward Project Context: Save project guidance once; new tasks match relevant guidelines to the prompt, inherit defaults, and let you inspect what the agent actually received.
- Unified Code Review: Read each result beside its original brief, combine related patches into one review, request another pass, and decide what enters the project.
- Named Account Profiles: Keep work and personal agent accounts separate with per-project defaults and per-account usage tracking.
- Agent Browser and Computer Use: A separate browser session per task lets agents navigate pages, fill forms, capture screenshots and run accessibility checks; Windows desktop control adds approved window clicks, typing and scrolling.
- Cross-Agent Messaging: Tasks share a project inventory with ownership, scopes and dependencies, and agents can send direct task messages or project broadcasts through a durable inbox.
Best for
- Running Experiments Side by Side: Try two different approaches to the same problem with different agents and compare the resulting patches before choosing one.
- Reviewing Agent Output Safely: Keep every generated change behind a human review step, with checks attached to the code they tested.
- Comparing Coding Agents: Assign the same brief to Codex, Claude Code and Grok to see which handles your codebase best.
- Separating Work and Personal Accounts: Use the right provider account per project without re-authenticating or risking cross-billing.
- Understanding a Change's Blast Radius: Use the codebase map to see which files a proposed change touches before merging it.
- Automating Verification: Let agents drive a sandboxed browser to fill forms, screenshot results and run accessibility audits as part of a task.