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Cambium

by jarmstrong158version 0.2.0i★ –iRuns on your computer
Registry nameio.github.jarmstrong158/cambium

Install

Overview

Description from the maker (original English)

Knowledge-lifecycle MCP: turn agent work into memory, recall it across projects, promote to org.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

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).
  • You fill in yourself: CAMBIUM_REPO, CAMBIUM_AGENT_ID, CAMBIUM_ORG_REPO

You need

  • PyPIPython’s uv installed (for the uvx 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": {
    "cambium": {
      "command": "uvx",
      "args": [
        "cambium-mcp"
      ],
      "env": {
        "CAMBIUM_REPO": "your-value",
        "CAMBIUM_AGENT_ID": "your-value",
        "CAMBIUM_ORG_REPO": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add cambium --env CAMBIUM_REPO=your-value --env CAMBIUM_AGENT_ID=your-value --env CAMBIUM_ORG_REPO=your-value -- uvx cambium-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "cambium": {
      "command": "uvx",
      "args": [
        "cambium-mcp"
      ],
      "env": {
        "CAMBIUM_REPO": "your-value",
        "CAMBIUM_AGENT_ID": "your-value",
        "CAMBIUM_ORG_REPO": "your-value"
      }
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "cambium": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cambium-mcp"
      ],
      "env": {
        "CAMBIUM_REPO": "your-value",
        "CAMBIUM_AGENT_ID": "your-value",
        "CAMBIUM_ORG_REPO": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • CAMBIUM_REPO env
    Absolute path to the project git clone cambium reads/writes. Defaults to the current repo (cwd git root) when unset.
  • CAMBIUM_AGENT_ID env
    Your unique agent id, attributed to captures/endorsements/promotions.
  • CAMBIUM_ORG_REPO env
    Path to the org knowledge repo clone (org scope). Omit to keep promotions at team scope.

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account jarmstrong158, 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 5688 servers in this category
  • Published to the registry more recently than 27% of the other 5688 servers in this category
  • Basic checks equal to or better than 100% of the other 5688 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 Cambium 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 (0.2.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) 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:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsGrowing★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

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.

cambium

_Part of the xylem stack._

The knowledge-lifecycle MCP that turns work your agents already did into compound, org-wide knowledge. cambium bridges two substrates that already exist — agentsync (what happened: claims, finishes, notes, changed files) and context-keeper (why: decisions, constraints) — and adds the three things neither has:

  1. `distill()` — turn events into memory *automatically* (passive capture)
  2. `recall()` — one federated read endpoint for every agent type (coding agent, Slack KB bot, SRE bot — same store, same call)
  3. `promote()` — graduate knowledge local → team → org as it earns trust

Named for the cambium layer of a tree: the thin living tissue where all growth happens.

Why a third MCP (and not a database)

Knowledge layers fail because they're a *side system* nobody calls. cambium's bet: capture and recall must be native tools in the agent's loop, and state must live in the substrate the work already lives in — git — not a separate service. Storage is an implementation detail behind recall():

ScopeLives inTrust gate
local /.cambium/knowledge.jsonnone — it's yours
teamknowledge.json on a dedicated cambium branch of the shared reporecalls ≥ N or an endorsement
orgknowledge.json in a dedicated org knowledge repoan endorsement required; optionally lands as a pull request — review is the gate, git revert is the undo

Team writes use the agentsync pattern: a private worktree under .git/ and git push as compare-and-swap, so concurrent agents never clobber each other.

Install

pip install -r requirements.txt      # just `mcp`

gh (GitHub CLI) is only needed for pull-request-mode org promotion.

Configure

Point an MCP client at the server — no env required to start:

{

"mcpServers": { "cambium": { "command": "python3", "args": ["/abs/path/to/cambium_server.py"] } } }

First contact is helpful, not cold. MCP servers can't start a conversation, so cambium teaches you through its own responses. Call `status()` (or any tool) before it's configured and instead of a bare env error you get structured guidance — what's set, what's missing, what each gap costs in plain terms, and the exact setup() call that fixes it:

{

"configured": false, "gaps": [ {"setting": "CAMBIUM_REPO", "cost": "no project repo → cambium has no substrate; every tool is unavailable", "fix": "setup(project_repo=\"/abs/path/to/your/clone\", agent_id=\"your-id\")"}, {"setting": "CAMBIUM_ORG_REPO", "cost": "org scope off → promotions stop at team; org-wide recall unavailable", "fix": "setup(project_repo=…, agent_id=…, org_repo=\"owner/knowledge or /abs/path/to/clone\")"} ], "next_step": "setup(project_repo=\"/abs/path/to/your/clone\", agent_id=\"your-id\")" }

`setup(project_repo, agent_id, org_repo?, org_pr?, team_branch?)` finishes the job: it validates the paths, scaffolds .cambium/ (and adds it to the repo's .gitignore), and writes a fallback config at ~/.cambium/config.json that the server reads when env vars are absent. It takes effect immediately — no restart. No secrets are written: the file holds only paths, ids, and flags, and lives outside any repo. If org_repo is a GitHub owner/name you haven't cloned locally, setup offers the exact `gh`/`git` commands to stand it up and leaves org scope off — it never creates or pushes a repo for you.

Env still wins. Any of the variables below, set in the MCP client config, overrides the config file per-key — the table is the full reference layer:

env varrequireddefaultmeaning
CAMBIUM_REPOyes—your project clone (local scope, agentsync + context-keeper substrates)
CAMBIUM_AGENT_IDyes—your unique agent id
CAMBIUM_REMOTEnoorigingit remote
CAMBIUM_GIT_TIMEOUTno25per-invocation git/gh timeout (seconds) so a stuck call fails fast instead of hanging the server
CAMBIUM_TEAM_BRANCHnocambiumteam-scope branch
CAMBIUM_AGENTSYNC_BRANCHnoagentsynccoordination branch name distill reads
AGENTSYNC_BOARD_REPOno\*—which repo holds the board — the same setting agentsync reads, so the two servers cannot disagree (see below)
CAMBIUM_ORG_REPOno—path to the org knowledge repo clone (org scope off without it)
CAMBIUM_ORG_PRnodirect push1 = org promotion opens a pull request
CAMBIUM_PROMOTE_RECALLSno3recalls needed for local→team
CAMBIUM_RELEASE_CAPTUREnooff1 = also capture agentsync claims at their done/released transition (see below)
CAMBIUM_CONFIG_FILEno~/.cambium/config.jsonoverride the fallback config path (mainly for tests)
Where the agentsync board lives (board addressing)

\* distill() reads finished agentsync claims off a coordination board. That board is a shared, long-lived team artifact — not a property of whichever project this session happens to be in — so cambium resolves its address independently of the session, using exactly the order agentsync itself uses:

  1. `AGENTSYNC_BOARD_REPO` — the explicit board address (env, or the same key in ~/.cambium/config.json). One setting configures both servers.
  2. `AGENTSYNC_REPO` — agentsync's legacy explicit pin.
  3. `CAMBIUM_REPO` — but *only if that repo actually holds the coordination branch* (real ref lookup: local head → remote-tracking ref → ls-remote).
  4. Otherwise: no board, reported loudly (next section) — never silently.

Why. Before this, cambium looked for the coordination branch in CAMBIUM_REPO while agentsync (unpinned) followed ~/.xylem/active_project.json. The two could point at different repos, and whenever the current project had never been provisioned neither found anything. distill() reported that as the bland string "no coordination branch found", callers treated it as normal, and the result was that distill imported zero agentsync claims across its entire lifetime — a three-legged design silently running on two legs.

A skipped source does not look like a completed one

distill()'s return now makes a miss impossible to read as a success:

  • top-level status becomes "distilled_with_warnings" (not "distilled");
  • top-level warnings carries a plain-language line per skipped substrate;
  • sources.agentsync is an object — {status, board_repo, board_source, branch, claims_seen, done_claims, imported, reason, fix} — so "there is no board", "the board is here and nobody has finished anything", and "imported 3" are three visibly different results rather than one empty number.

status() reports the same under substrates.agentsync_board.

Org setup: create one (private) repo, e.g. github.com/you/knowledge, with an empty {"items": []} in knowledge.json; everyone who should read org knowledge clones it and points CAMBIUM_ORG_REPO (or setup(org_repo=…)) at their clone. cambium manages that clone (it hard-syncs it) — dedicate it, don't work in it.

Tools

`capture(content, type, kind, why, tags, valid_while)` — save a knowledge item to local scope (types: memory | need | skill). Manual path. valid_while optionally names the premise the item depends on, so a dead assumption is spottable later (see *Machine-maintained documentation entropy*).

`record_need(content, why, tags)` — first-class needs ("we're missing X"), promotable like anything else so recurring wants surface at team/org level.

`distill()` — the automatic path. Reads agentsync's coordination branch (every *currently done* claim: task + note + changed files → an outcome memory) and context-keeper's .context/ (active decisions & constraints, rationale and dec-NNN provenance preserved). Idempotent — wire it to a session-end or post-commit hook and capture becomes passive.

Release-time capture (opt-in, `CAMBIUM_RELEASE_CAPTURE=1`). agentsync keys claims by agent id and deletes a claim from live state the instant it is released or re-claimed — it exposes no hook or event, only the rewritten claims.json on the branch. So a claim that completes and then churns before a full distill runs against it is silently lost. With the flag on, each distill also remembers the last-seen claim per agent and captures any that has *churned away* since the previous run — reconstructing it from that snapshot, through the same dedupe watermark, so a claim captured at release time and again in a later full distill never double-imports. Fire distill() on completion events (a post-commit / session-end hook) and completed work is captured at its transition instead of only when a distill happens to catch it live.

What this is not: it is passive capture *at the moments distill runs*, not exhaustive reconstruction. The guarantee is precise — *if a distill sweep observes a claim while it is done (or carries a note), that knowledge is captured even if the claim later churns.* The residual gap: a done state that is created and churned away entirely between two sweeps (e.g. cambium wasn't running) is never observed, and only agentsync's git log still holds it. Walking that log to reconstruct such claims exhaustively is a possible follow-up (the history survives — agentsync's history() reads it), deliberately left out of this change.

`import_memory(source, path)` — ingest an external memory export into cambium as local-scope, provenance-tagged knowledge items (see Import below). Read-only against the source; imported items are not auto-promoted.

`recall(query, scope, limit)` — federated search across local+team+org. Every hit increments the item's recall counter (the trust signal promotion feeds on) and records cross-project use. Abstains honestly: below the relevance floor it returns no_confident_match: true instead of confident-looking noise. Each result carries endorsed_as — the item's endorsement notes surfaced as first-class context, since for a promoted item that is where its cross-project meaning was written.

`endorse(item_id, note)` — vouch for an item. Fast-tracks local→team; required for team→org.

`promote(item_id, to_scope, force, org_content)` — no args: scan-and-promote all eligible local items to team. With to_scope="org": push to the org repo, or open a PR when CAMBIUM_ORG_PR=1 (the team copy stays, annotated, until the PR merges). Promotion stamps last_verified — promotion *is* a verification. Generalization gate: org scope is read by every project, so a body that reads project-specific (names a file, a test_* id, a dec-/con-NNN ref, or its own origin project) is refused at the org boundary — restate it as the cross-project rule via org_content= (the concrete body is kept as example) or force=True to override. The refusal hands back the endorsement note as a ready draft. Mirrors the endorsement gate; the safe path is the easy path.

`generalize(item_id, org_content, note)` — the remediation counterpart of the gate: restate an already-promoted item's body as the cross-project rule *in place*, keeping the concrete version as example. For items that reached org before the gate (or were forced past it) — the ones review_promotions() lists under org_needs_generalization. Omit org_content to fall back to the item's latest endorsement note. Writes through the org CAS path (direct, or a single shared cambium/generalize PR branch when CAMBIUM_ORG_PR=1, so repeated calls batch into one reviewable PR); idempotent.

`verify_entry(item_id, note)` — confirm an entr

Only the beginning is shown; read the rest in the repo

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