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  1. Home
  2. 🧠 Knowledge & Memory
  3. Tribal
Tribal logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 8:46:08 PM

Tribal

User RatingsBe the first to rate and review this MCP server!
View Repository9 GitHub StarsTotal stargazers on GitHub for the source repository (9 stars).Visit Website
knowledgememorypostgressemantic-searchmcp

Self-hosted MCP server providing semantic memory of engineering knowledge backed by Postgres with pgvector.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ā–¾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "tribal-memory-tribal": {
      "command": "npx",
      "args": [
        "-y",
        "skills"
      ]
    }
  }
}

šŸ’” Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This server captures and serves an engineering team's tribal knowledge—tacit decisions, reasoning, and heuristics behind code—using semantic compression. It runs as a Model Context Protocol server, ingesting text on demand and exposing a graph of interconnected knowledge items. It is designed for teams and AI agents needing to query and preserve useful project knowledge beyond code and tickets. The server requires Postgres 14+ with pgvector and supports local or cloud embedding and inference providers.

Use cases

•Capture tacit engineering decisions and reasoning
•Query interconnected project knowledge semantically
•Preserve useful heuristics and bug fixes for team reference
•Integrate tribal knowledge into AI agent workflows
•Bootstrap knowledge base from git repositories

Key features

•Postgres-backed semantic memory with pgvector
•Graph of knowledge items linked by support, contradiction, refinement
•MCP server interface for agent integration
•Supports local Ollama or cloud embedding/inference providers
•Command-line tools for bootstrap, check, and project registration

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Tribal.

Extracted Tool Capabilities
Postgres-backed semantic memory with pgvector
Graph of knowledge items linked by support, contradiction, refinement
MCP server interface for agent integration
Supports local Ollama or cloud embedding/inference providers
Command-line tools for bootstrap, check, and project registration

Documentation Overview

Tribal: semantic memory served over MCP

Tribal

Semantic compression for project knowledge.

Release Build License Docker Homebrew

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:

Terminal
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)

bash
brew install tribal-memory/homebrew-tap/tribal

Shell installer (macOS or Linux)

Terminal
curl --proto '=https' --tlsv1.2 -LsSf \
  https://github.com/tribal-memory/tribal/releases/latest/download/tribal-installer.sh | sh

Docker Compose (bundled Postgres)

bash
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:

bash
tribal bootstrap

Prerequisites

  • Postgres 14 or higher with the pgvector extension.
  • 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:

bash
tribal bootstrap

Flags worth knowing:

  • --project-path DIRECTORY includes project registration in the bootstrap composition. Omit it when initialising an unscoped deployment.
  • --transport stdio|http|sse chooses the integration receipt's connection shape. Omission follows the configured transport.
  • --auth oauth|persisted-bearer selects network authentication. Exporting a bearer is explicit and is not available for stdio.
  • --json emits 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.

bash
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:

bash
tribal check --providers

For scripted consumers, --json emits a structured record. Every failed check includes a remediation field with the exact next step:

bash
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 stdio to 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, then docker compose up. The volume is recreated on the next start.
  • Stale project context. If TRIBAL_PROJECT_ID is set in your environment to a project that no longer exists, unset it or re-run tribal bootstrap against the current directory's git remote.
  • Missing provider env vars. tribal check --providers names 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 tribal for Homebrew installs, the installer's removal script for the shell-installer path, or docker compose down -v for 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.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
9
Stargazers on the source repository.
npm downloads
35M
Package downloads in the last 30 days.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Tribal

Tribal requires Postgres version 14 or higher with the pgvector extension installed.

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Technical Specs & Signals

Category🧠Knowledge & Memory
PricingBring your own API key (usage-based cost)
More technical detailsExpand ā–¾
TransportSTDIO
RuntimeNode.js
AuthAPI key
LicenseElastic-2.0
Last updatedAug 9, 2026
9/10 checks healthy over the last 32d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars9
GitHub Star CountTotal stargazers on GitHub representing community popularity (9 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 6, 2026
npm downloads35,454,130/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
56Quality signal: Good Ā· 56/100How this signal is calculated ā–¾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity8/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Scanned 22d ago via OSV.dev Ā· skills (npm)

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