knowledgememorysemantic-searchteam-collaborationgit-integration
Persistent shared AI memory brain with semantic search and team knowledge management for multiple MCP clients.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
Automated check passed— started and listed 126 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON ▾
Client Config & Setup
Choose your client or environment
Target File:
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Overview
Use cases
Brief AI sessions with prior context and lessons
Recall best solutions and expert knowledge on topics
Share and confirm lessons across team members
Analyze root causes with causal knowledge graphs
Detect knowledge gaps and monitor brain health
Key features
Session briefing and summary with lesson extraction
Hybrid BM25 and semantic search across 11 languages
Team roles, lesson confirmation, and audit trail
Expertise and collaboration graphs with skill gap detection
Brain import/export and shareable snapshots
Integration with git history and CI logs for automatic learning
Capabilities & Tool Schemas (126)
Inspect callable tools, capabilities, and parameters exposed to AI agents by Cachly MCP.
list_instancesList all your cachly cache instances with their status and connection details. Read-only. Returns an array of instance objects — each with id, name, tier, status, region, RAM, and redis:// connection string. Returns an empty array if no instances exist. No pagination: all instances are returned in one call (typical accounts have < 20). Use this first to discover instance UUIDs required by get_instance, cache_get, cache_set, and all other cache tools. Use get_instance to retrieve full metadata for a single instance.
create_instanceCreate a new managed Valkey/Redis cache instance on cachly.dev. Free tier provisions in ~30 seconds. Paid tiers return a Stripe checkout URL. Available tiers: free (25 MB), dev (200 MB, €19/mo), pro (900 MB, €49/mo), speed (900 MB Dragonfly + Semantic Cache, €79/mo), business (7 GB, €199/mo).
get_instanceGet full metadata for a specific cache instance: name, tier, status (provisioning / running / paused), region, RAM limit, Redis connection string, created_at, and expiry. Read-only. Returns an error if the instance_id is not found or belongs to another account. Call list_instances first to discover valid UUIDs. Use get_connection_string instead if you only need the redis:// URL for your app config.
get_connection_stringGet the Redis/Valkey connection string (redis:// URL) for a running instance. Use this to configure your application or set environment variables.
delete_instancePermanently delete a cache instance. Deprovisions the Kubernetes workload and removes all data. This action is irreversible.
cache_getGet a value from a running cache instance by key. Returns the stored value (string or deserialized JSON object) or null if the key does not exist or has expired. Read-only — no side effects. Use cache_mget when you need multiple keys in one round-trip. Use cache_exists to check existence without retrieving the value. Use semantic_search when you need fuzzy/vector search across stored values.
Documentation Overview
🧠 cachly AI Brain — MCP Server
ChatGPT and Claude remember your conversations.
cachly remembers your codebase.
The bug you fixed. Why you chose Postgres. The deploy step that always breaks — and everything your teammates learned. It stays when someone leaves the team, and it comes along when you switch assistants.
⚡ Get your free Brain → cachly.dev
Free forever · no credit card · 1-command setup · German servers · GDPR
The story you already live every day
You are a good engineer. You want to ship, not babysit a forgetful assistant.
But every session starts at zero. Your AI doesn't remember the race condition you chased for three hours on Tuesday. It doesn't know your deploy gotchas. It can't tell you that Carol already solved this exact bug in March — because Carol's knowledge lives in Carol's head, and yours in yours.
So you re-explain. You re-research. Your team makes the same mistake in five different branches. And when someone leaves, their hard-won knowledge walks out the door with them.
The villain isn't your AI. It's amnesia. Context death between sessions, and knowledge silos between people. The average developer loses ~45 minutes a day re-establishing context that should already exist.
You don't need a smarter model. You need a memory that doesn't reset — and one that your whole team shares.
Meet your guide
cachly is the brain layer that sits under whatever AI you already use. We've watched hundreds of teams lose the same knowledge the same way, and we built the fix:
- It learns automatically — from every commit, every fix, every session. No extra calls.
- It arrives pre-briefed — your AI opens each session already knowing your stack.
- It's shared — one engineer's solved bug becomes the whole team's reflex.
- It's provable — 78.6 % Precision@1 on an external labelled corpus, with a CI gate that fails the build below 71.0 % (see the benchmark). A claim without a number is marketing; a number without a gate is a screenshot.
- It's neutral — speaks MCP, so it works with Claude, Cursor, Copilot, Windsurf, Cline, Zed. Switch models anytime — your brain stays.
We're not the hero of this story. You are. cachly is the thing that makes you the engineer whose AI never forgets and whose team compounds knowledge instead of losing it.
Taste it first — no account, no risk
Run it in any project folder. It reads YOUR git history and shows what your AI would know — your bugs fixed, your patterns, your past decisions. Nothing leaves your machine.
Like what you see? Make it permanent in the next step.
Brain-first — Semantic Cache as Proof-Point
cachly is not a semantic cache with a brain bolt-on. The Brain is the product. The Semantic Cache is the proof-point — it shows ROI in dollars from day one, with zero trust required. It opens the door. The Brain is why teams never leave.
| Wedge — Land | Moat — Retain | |
|---|---|---|
| Feature | Semantic Cache | AI Brain (Lessons, Recall, Team-Sharing) |
| Value | Measurable cost savings from day one | Compounding team intelligence |
| Metric | Cache-hit rate, $/month saved | Lessons retained, WoW trend, recall quality |
| Analogy | Datadog APM (surfaces the problem) | Stripe (becomes critical infrastructure) |
The org-level advantage: Brain lessons and cache hits are shared across the whole team — one person's fix becomes every agent's reflex. Anthropic Projects Memory is per-user and model-locked. cachly is team-wide and model-neutral. That's the structural moat no first-party tool can build.
Setup — pick the shortest path for your editor
Claude Code — two lines
Claude Code declares the MCP server for you; there is no JSON to write and no
path to set. Paste your brain ID once with /plugin configure cachly-brain@cachly
and you are done. (From v0.10.139 the server sets itself up on first use —
an anonymous 14-day trial brain, nothing to copy.)
Check it worked with claude mcp list — you should see
plugin:cachly-brain:cachly … ✔ Connected. Note that claude plugin details
reports MCP servers (0) even when the server is running; it does not count
them.
VS Code — one click
Install the cachly Brain extension. It signs you in silently and creates your brain — no account form.
JetBrains — one click
Install Cachly Brain
from the JetBrains Marketplace (IntelliJ, PyCharm, GoLand, WebStorm, Rider).
Status bar, brain health and the lessons view live in the IDE; the source is
at cachly-dev/cachly-intellij.
The npx … autopilot path below also configures JetBrains AI Assistant.
MCP Registry — for any client that reads it
The server is listed in the official MCP Registry
as io.github.cachly-dev/mcp-server, every release, same day. Clients that
browse the registry (Claude Desktop, Goose, VS Code's MCP gallery and others)
find it there by name; the entry points at this npm package.
Anything else — one command
Autopilot does everything in a single command: it auto-detects every AI editor you use, writes the MCP config, signs you in via browser device-flow (one click, no password, no credit card), and bootstraps your brain from git history. Restart your editor and your AI arrives pre-briefed — every session, automatically.
Already inside Claude / Cursor / Copilot? Paste this to your AI and it configures everything itself:
Our agreement with you: Free forever tier. GDPR, EU servers. No model lock-in —
leave anytime and take your data: npx @cachly-dev/mcp-server@latest export writes
every lesson to lessons.md (to read) and lessons.jsonl (to reuse). Code excerpts
are stored only if you call index_project yourself — and only on your own EU
instance.
What changes the moment you turn it on
| The moment | Without cachly | With cachly |
|---|---|---|
| Session start | "What's your architecture again?" | "Ready. 23 lessons. Last session: deployed API." |
| A known bug returns | Re-researches from scratch | "You fixed this March 12 — here's the exact command." |
| You open an unfamiliar file | Cold start | "Carol fixed 3 bugs here. Related: fix:stripe-retry." |
| A teammate leaves | Their knowledge leaves too | Their lessons stay, attributed, searchable |
| New hire, day one | Weeks to onboard | setup → full team context instantly |
| Pre-deploy | Hope nothing breaks | Brain predicts failure risks from past patterns |
This is the transformation: from the engineer who re-explains everything every morning → to the team whose collective brain never forgets and gets sharper with every commit.
cachly vs. Claude's built-in memory
Anthropic now ships memory for Claude — and it's genuinely good for one developer, using only Claude, alone. That's not the game we're playing. Here's the honest map:
Related MCP Servers
Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
GitHub stars
2
Stargazers on the source repository.
Last commit
6d ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
126
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.
Reviews
No reviews yet — be the first to share how this listing worked for you.
Frequently Asked Questions about Cachly MCP
AllMCPs Directory Badge
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
Badge Style:
Live Dynamic SVG Preview
Markdown (GitHub README)
[](https://allmcps.com/mcp/cachly-dev-cachly-mcp)HTML Embed
<a href="https://allmcps.com/mcp/cachly-dev-cachly-mcp"><img src="https://allmcps.com/api/badge/cachly-dev-cachly-mcp?style=directory" alt="Cachly MCP on AllMCPs" /></a>