tribal
Self-hosted semantic memory over MCP for an engineering team's tacit knowledge. Rust, Postgres + pgvector.
Install / Use
claude mcp add tribal-memory -- npx -y github:tribal-memory/tribalIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of tribal
tribal scores 75/100 on our quality scale, 843rd of 963 AI & Machine Learning skills we index.
Its MCP Server is 9.7 KB long, well organised into 10 sections with 9 code examples: a thorough specification that gives an agent plenty to work with.
It has 10 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 3 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-10-18 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 83/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
tribal compared with similar skills
All 4 of these similar skills score higher than tribal; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| tribal (this skill)by tribal-memory | 75 | 10 | 3mo ago | MCP Server |
| claude-memby thedotmack | 100 | 113.6k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.3k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 91.0k | 11d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 79.0k | today | CLAUDE.md |
Frequently asked questions
- How do I install tribal?
- Run
claude mcp add tribal-memory -- npx -y github:tribal-memory/tribal. The install tabs above show the steps for each supported agent. - Which AI agents does tribal work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is tribal safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 83/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is tribal still maintained?
- The repository was last updated about 3 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubTribal
Semantic compression for project knowledge.
Tribal captures the engineering knowledge that does not get written down in code or tickets. The reasoning behind a load-bearing decision, the heuristic someone keeps reaching for, the breakthrough that closed a gnarly bug. It runs as a Model Context Protocol server, ingests text on demand, and exposes a graph of items connected by what they support, contradict, or refine. Your agent harness talks to it the same way it talks to any other MCP tool.
Tribal is not trying to remember everything. It preserves what remains useful after the work is done.
Quick start
Start with the skills. Tribal runs inside your agent, and the skills teach it to install, verify, wire, and troubleshoot Tribal. Installing them and letting the agent drive is the most reliable path:
npx skills add tribal-memory/skills
Then ask your agent to set Tribal up. The steps below are what the skills walk it through, or what to run by hand. The agent can help either way.
If you plan to use a cloud provider (OpenAI or Anthropic), export its API key in your shell before you launch the agent harness, so the harness and the Tribal binary it spawns inherit it. A key exported into a terminal the harness is already running in is not picked up until you relaunch. Setting it up front removes a lot of the early configuration friction.
Install Tribal using whichever path fits your environment. Pick one:
Homebrew (macOS)
brew install tribal-memory/homebrew-tap/tribal
Shell installer (macOS or Linux)
curl --proto '=https' --tlsv1.2 -LsSf \
https://github.com/tribal-memory/tribal/releases/latest/download/tribal-installer.sh | sh
Docker Compose (bundled Postgres)
tag=$(curl -fsSL https://api.github.com/repos/tribal-memory/tribal/releases/latest | jq -r .tag_name)
mkdir tribal-docker && cd tribal-docker
curl -fsSL "https://raw.githubusercontent.com/tribal-memory/tribal/$tag/docker-compose.yml" -o docker-compose.yml
docker compose up
The compose file pins the image to a specific release, so fetch it from a release tag rather than reusing an old checkout. The stack bundles its own Postgres and bootstraps itself on first start. To point a stage at a cloud provider instead of a local Ollama, configure .env before the first docker compose up; the installing-tribal skill walks through it.
For the Homebrew and shell-installer paths, bootstrap from inside a git repository. This runs setup, registers the repository as a project, mints a bearer token, and prints the MCP config snippet your harness will need:
tribal bootstrap
Prerequisites
- Postgres 14 or higher with the
pgvectorextension. - A provider for embeddings and inference. Either a local Ollama installation with the required models, or API keys for a supported cloud provider set in your environment.
tribal bootstrap never calls a provider, but it does validate configuration, so a configured cloud provider's API key must already be in your environment when you run it. Provider reachability for ingest is verified separately by tribal check --providers.
Setting up
tribal bootstrap is the canonical first run. It asks the local manager to initialise the configured database, apply model and graph settings, optionally register a working tree, and ensure a namespaced default credential. It is safe to run again against the same durable state:
tribal bootstrap
Flags worth knowing:
--project-path DIRECTORYincludes project registration in the bootstrap composition. Omit it when initialising an unscoped deployment.--transport stdio|http|ssechooses the integration receipt's connection shape. Omission follows the configured transport.--auth oauth|persisted-bearerselects network authentication. Exporting a bearer is explicit and is not available for stdio.--jsonemits a structured JSON record of everything that happened. Useful for scripting and for piping into the diagnostic flow described below.
Bootstrap composes the same typed manager capabilities available under tribal database, tribal project, tribal token, and tribal integration; those commands never open the database or credential store independently.
Verifying readiness
tribal check runs the core diagnostic suite: configuration, database reachability, migration state, project resolution, token validity, advertised URL reachability, and binary uniqueness on PATH. It exits non-zero if any check fails.
tribal check
Add --providers to extend the suite with fatal probes of the embedding and inference providers. Run this before your first ingest to confirm the system can do real work:
tribal check --providers
For scripted consumers, --json emits a structured record. Every failed check includes a remediation field with the exact next step:
tribal check --json
Connecting to your agent harness
The canonical MCP config for any compatible harness comes from tribal integration mcp-config. On a local HTTP or SSE deployment the default OAuth document is URL-only. Pass --auth persisted-bearer to make the secret-bearing export explicit for a harness that only supports an Authorization header. The stdio document carries no token and starts explicitly unscoped or with the selected project context.
For per-harness translations, ask your agent to invoke the installing-tribal skill. It walks through wiring Tribal into your harness and produces the exact command to run.
Using Tribal
Day-to-day use happens through your harness. Once the MCP server is wired up, the harness can ingest knowledge, query it, traverse the graph, and rate retrieval quality.
The using-tribal skill teaches your harness when and how to call each tool, and how to phrase ingests so they survive in the graph long after the work is done. It activates whenever the harness sees a signal that prior context might be relevant, or that something worth preserving has just happened.
Recovery
Most operational issues fall into a small set of patterns:
- Port already in use. Tribal exits with the conflicting address in the error message. Free the port, or switch to
--transport stdioto bypass network binding. - Bad credentials state. Re-run
tribal bootstrap; the manager recovers or replaces the namespaced pending/stable credential pair transactionally. - Corrupted Docker volume. Stop the stack with
docker compose down -v, thendocker compose up. The volume is recreated on the next start. - Stale project context. If
TRIBAL_PROJECT_IDis set in your environment to a project that no longer exists, unset it or re-runtribal bootstrapagainst the current directory's git remote. - Missing provider env vars.
tribal check --providersnames which provider stage is failing and walks the resolution chain. Set the missing variable and re-run.
Logs are written to standard error. Every command that has a useful structured form supports --json; the structured output is more amenable to parsing than the human stderr stream.
To re-bootstrap cleanly without losing your knowledge graph, run tribal bootstrap again. It will reuse the existing project if the git remote matches, mint a new bearer token, and re-emit the MCP config snippet.
Troubleshooting
tribal check is the first stop for any operational issue. It surfaces failures with a remediation field describing the next action in plain prose. Pass --json when you need to consume the structured form.
When tribal check reports ok: true and a problem is still visible, the issue is usually network-level rather than Tribal itself. The most common pattern is a VPN or firewall sitting between the binary and the database; MCP errors look like Tribal is down even though the database is what's broken. Confirm connectivity to the configured database before assuming Tribal is at fault.
For runtime failure modes that fall outside the check suite (worker death, transport-layer errors, prompt loading failures), the using-tribal skill bundles a reference covering each pattern. Install it via the Quick start one-liner if you haven't already.
Removing Tribal
Manual steps, in any order:
- Remove the binary.
brew uninstall tribalfor Homebrew installs, the installer's removal script for the shell-installer path, ordocker compose down -vfor the containerised path. - Delete the namespaced credential directory at
$XDG_CONFIG_HOME/tribal/credentials/. - Drop the Postgres database Tribal was using.
- Remove the skills with
npx skills remove installing-tribal using-tribal.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
