Context7
by upstash
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Computer or cloud★ 64,224MITUpdated today
Install
Dreamd
Overview
Description from the maker (original English)
Auditable agent memory: lessons cite their sources, and bad memories can be traced and removed.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Search & AI memory
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- npmNode.js installed (for the npx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"dreamd": {
"command": "npx",
"args": [
"-y",
"dreamd-mcp"
]
}
}
}Run this in your terminal
claude mcp add dreamd -- npx -y dreamd-mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"dreamd": {
"command": "npx",
"args": [
"-y",
"dreamd-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"dreamd": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"dreamd-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account botzrDev, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7248 servers in this category
- Published to the registry more recently than 94% of the other 7248 servers in this category
- Basic checks equal to or better than 100% of the other 7248 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Dreamd safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (1.2.2) reached the registry 2 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
What can I use instead?
In the same category: Context7, Codebase Memory, Exa
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Codebase Memory
by DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Runs on your computer★ 48,148MITUpdated 20 days ago
Install
Exa
by exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Runs in the cloud★ 5,213MITUpdated last month
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
dreamd
Agent memory you can audit. When a memory goes bad, trace it to its source, see what it fed, and remove it.
dreamd is local-first, long-term memory for AI agents. Every memory is a line in a file in your repo, every lesson your agents learn cites the events it came from, and each dream cycle commits its lessons to git. When an agent acts on something wrong, you can find the memory that caused it, see which lessons it fed, and take it out, with a receipt.
npx -y dreamd-mcp setup # scaffold .agent/ and wire your harnessnpx -y dreamd-mcp # MCP server (stdio): what the harness spawns
Recorded live on dreamd 1.2.0, sped up 1.5x: blame finds the event behind a bad answer, forget removes it with a receipt, and the same query comes back without it. Tape: docs/assets/blame-forget.tape.
Works today with Claude Code, Cursor, Cline and other MCP-aware harnesses. Self-hosted, single binary, Apache-2.0 core.
If you want agent memory you can trace and undo, star the repo to follow releases. When a memory goes wrong, an issue with the blame output helps us fix it.
Why auditable memory
Memory is the layer of an agent stack you usually can't see into. A prompt can be read and a model can be swapped, but when memory goes wrong there is rarely a way to tell what the agent believed, where that belief came from, or what else it touched.
That matters more now that memory is an attack surface. The OWASP Top 10 for Agentic Applications lists memory and context poisoning (ASI06): an attacker, a bad tool result or a plain mistake plants a "fact" that the agent keeps acting on in later sessions. The defenses OWASP points to start with knowing the source of every memory and being able to remove one cleanly (OWASP agentic top 10).
dreamd is built for that response:
| You need to | dreamd gives you |
|---|---|
| See what drove an answer | dreamd blame lists the stored memories behind a recall, with ids, timestamps, source and score. dreamd recall --explain prints the salience factors for each hit |
| Know where a lesson came from | Every lesson in LESSONS.md cites the episodic events it was promoted from, and the provenance ledger records which event fed which lesson and index entry |
| Check the record is consistent | dreamd doctor --provenance recomputes the ledger's Merkle root and lists orphan, missing and corrupt edges. Read-only |
| Remove a bad memory | dreamd forget removes the event and the lesson state that names it. --dry-run shows what would change; --proof writes a forget-receipt/1.0 file |
| Review what agents learned | .agent/ is committed with your code, and each dream cycle commits its output as dreamd: cycle YYYY-MM-DD. Review new lessons with git diff or in a pull request, and undo a cycle with git revert |
| Read everything yourself | Plain JSONL and Markdown. cat, grep and git log work on every byte |
What dreamd does not do. It does not detect or block poisoned writes, and it does not filter injected lesson content (SECURITY.md). source_harness is asserted by the caller, not verified. The provenance ledger and the forget receipt are unsigned, and there are no trust labels yet. dreamd makes bad memory traceable and removable; it does not make it impossible. See Roadmap for what comes next.
The audit loop in four commands
Say an agent keeps repeating advice you know is wrong.
# 1. Find the memories behind itnpx -y dreamd-mcp blame "deploy without tests" --explain
2. Check the lesson it came from and what that lesson cites
cat .agent/semantic/LESSONS.md npx -y dreamd-mcp doctor --provenance
3. Preview, then remove the bad event (stop the daemon, npx -y dreamd-mcp watch, first; forget refuses while it runs)
npx -y dreamd-mcp forget evt_... --dry-run npx -y dreamd-mcp forget evt_... --proof forget-receipt.json
4. Review the change like code
git diff .agent/
After a forget, doctor --provenance reports the removed event's old ledger edges as orphans and exits 1. That is expected: the ledger is append-only, so it keeps the record that the event once existed.
To undo a whole dream cycle instead, git revert its dreamd: cycle commit with the daemon stopped, then run npx -y dreamd-mcp doctor --repair to rebuild the recall index.
Install
npm (recommended)
npx -y dreamd-mcp setup # scaffold .agent/ and write the harness MCP confignpx -y dreamd-mcp # MCP server (stdio): your harness spawns this
stdio is the default transport. dreamd mcp --bind 127.0.0.1: is an opt-in Streamable HTTP server at /mcp. It is unauthenticated, and it is only in source builds with --features mcp-http. See docs/mcp-transports.md.
dreamd needs a project root sentinel (.git/, Cargo.toml, package.json or pyproject.toml).
setup prompts when it has a TTY. In scripts and non-interactive shells, pass --yes --harness claude|cursor|both (--harness none or --no-write-mcp scaffolds without touching any MCP config).
Cargo / from source
git clone https://github.com/botzrDev/dreamd.gitcd dreamd cargo install --path crates/dreamd-cli
See CONTRIBUTING.md for the full dev setup.
Quick start (under a minute)
If ~/your-project is a brand-new folder, run git init first.
cd ~/your-projectnpx -y dreamd-mcp setup
Optional: shared daemon, recommended when several agents write
npx -y dreamd-mcp watch
Reload your harness. setup already wired the dreamd MCP server, so the harness spawns npx -y dreamd-mcp itself.
Ask the agent to search memory for something it learned earlier. It calls search_nodes and recalls prior context, with the source harness on every hit.
cat .agent/episodic/AGENT_LEARNINGS.jsonlnpx -y dreamd-mcp dream --dry # preview the lesson the next cycle would write npx -y dreamd-mcp doctor
The npm shim does not put dreamd on PATH. Use npx -y dreamd-mcp on the npm path, or cargo install --path crates/dreamd-cli for the dreamd binary. From 1.2.1 the shim forwards every dreamd command; the 1.2.0 shim did not forward recall, score, status, archive and migrate.
Adapters: Claude Code · Cursor · Cline
Recorded live, sped up 1.5x: Claude Code writes the lesson, OpenCode reads it back through the same .agent/ folder. Tape: docs/assets/demo.tape.
How agents learn
Agents write episodes (what happened, how painful it was, how important) through MCP append_node. The dream cycle clusters episodes by skill_action and promotes a recurring pattern into a lesson in LESSONS.md. With an API key it composes the lesson with an LLM under a $0.10 per-cycle spend cap; without one it writes a deterministic lesson and makes no network call. Either way the lesson cites the events it came from, and every output is staged and committed through one redo WAL, so a crash leaves the store as it was or rolls the cycle forward.
Recall ranks episodes and lessons with BM25 × salience (age decay, pain, importance, recurrence). Recall is deliberately lexical; vector recall is not shipped (docs/vectors.md). Formula: docs/salience.md.
What dreamd writes
| Location | Contents | Commit? |
|---|---|---|
/.agent/ | Episodic JSONL, semantic lessons, personal prefs | Yes (this is the shared memory) |
/.agent/.dreamd/ | Local index, daemon state, config template, provenance ledger | No (gitignored by init) |
~/.agent/registry.toml | Which projects have a store | No |
~/.agent/dreamd.sock | Daemon API socket (while running) | No |
setup scaffolds the store by calling init, then writes the harness MCP config. Both are idempotent. To uninstall from a machine, run npx -y dreamd-mcp uninstall. On a tty it waits for y; pass --yes in a script. Without a tty and without --yes it exits 2 and changes nothing. Project .agent/ stores are left in place. npx -y is npx's flag, not dreamd's --yes. npx -y dreamd-mcp init --uninstall-project drops only the registry entry; dreamd init puts it back and does not rewrite the store.
All inspection commands
The MCP surface is two tools (search_nodes, append_node). Everything else is CLI over the same files. dreamd --help is the reference for flags.
| Command | What it does | |||||
|---|---|---|---|---|---|---|
dreamd recall | Ranked search as a markdown table. --explain prints the salience factors per hit; --without / --without-cluster drop hits before top-k, so you can see the answer without a suspect memory | |||||
dreamd blame | Which stored memories drove a query's ranking: id, timestamp, skill_action, bm25, salience, total, layer. --json for one compact array | |||||
dreamd score | Top memories by salience alone, no query | |||||
dreamd salience-drift | Salience distribution, top clusters, and drift against the snapshot from seven days earlier. See docs/observability.md | |||||
dreamd dream --dry | Print the LESSONS.md the next cycle would write, without writing | |||||
dreamd forget | Remove one episodic event and the lesson state that names it. --dry-run writes nothing; --proof writes a forget-receipt/1.0 file (a receipt, not a signed proof). Refuses while the daemon is running | |||||
dreamd doctor --provenance | Recompute the provenance ledger's Merkle root and list orphan edges, missing edges and corrupt lines. Read-only. See docs/provenance.md | |||||
| `dreamd memory branch\ | checkout\ | branches\ | delete\ | diff\ | bisect` | Deprecated in 1.2.0, removed in 2.0. .agent/ is plain files, so use git. See docs/branching-guide.md |
Architecture (one paragraph)
Agents talk to dreamd over MCP. On Linux and macOS the MCP server proxies to a single-writer daemon (dreamd watch) over HTTP on a Unix domain socket, or runs in-process when no daemon is present. On Windows it proxies to loopback dreamd watch and exits 2 when that daemon is down. One writer lock covers every process that writes a project. The coordinator appends to AGENT_LEARNINGS.jsonl and feeds a Tantivy BM25 index; recall ranks hits with the salience formula, and each hit carries source_harness and skill_action. Details: ARCHITECTURE.md · SPEC.md · docs/http-api.md. Warm recall latency (local Criterion benches) is in PERF.md.
Roadmap
Direction, not dated commitments. Full view: ROADMAP.md.
- Trust labels. A label on every memory saying where it came from and how far to trust it, joined along provenance edges, so a lesson from an untrusted source can't drive a privileged action. Needs its own spe
Only the beginning is shown; read the rest in the repo