
Pindoc
io.github.var-ggPublished by GitHub account var-ggv0.2.0Updated Oct 24, 2026
Code-pinned team memory for AI coding agents — typed artifacts, MCP-native, self-host.
Overview
Self-hosted project memory for AI coding agents: turns agent findings into typed, code-pinned artifacts that teammates and future agents can search.
- What you can do
- Detect the workspace and resolve the project slug for the current repository, with an installable harness that records the slug in a project file. Read the task queue and pull task context before editing code. Propose typed artifacts such as decisions, analyses, debug paths, task closeouts and verification notes, pinned to commits, files, line ranges, URLs or related artifacts. Update task acceptance and closeout state. Upload and attach assets such as inline images to artifacts. Search project memory semantically through a bundled embedding provider.
- When to use it
- For teams running AI coding agents across multiple sessions who want debugging paths, decisions and analyses to persist as reviewable team knowledge instead of dying with the chat. Useful when several agents or teammates need shared, commit-linked context before editing code.
- Requirements
- Runs as a local Docker Compose stack (Docker 27+, about 2 CPU cores, 4 GB RAM and 5 GB disk recommended) bringing up Postgres with pgvector, the daemon and a Reader UI. Requires PINDOC_DATABASE_URL (Postgres connection string) and outbound HTTPS on first run to cache the bundled embedding model. MCP clients connect to the daemon's HTTP endpoint at 127.0.0.1:5830/mcp; PINDOC_BIND_ADDR defaults to loopback.
Installation
In SourceWeft
- Open Pindoc in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Pindoc
[English README] [Korean README]
Code-pinned team memory for AI-assisted development. Agents write the durable record; humans review, discuss, and steer.
Pindoc is a self-hosted project memory system for teams working with AI coding agents. It turns useful agent discoveries into typed artifacts: decisions, debugging paths, task closeouts, verification notes, and code-linked analyses. Every artifact is scoped to a project area and pinned back to commits, files, URLs, resources, or related Pindoc artifacts.
It is still the wiki you never type into, but the point is not automation for its own sake. Pindoc keeps the parts of agent work that teammates and future agents can reuse.
Why It Exists
AI coding sessions are productive, but team context still falls through the cracks:
- a debugging path dies with the terminal session,
- the same decision is re-explained to every new agent,
- useful analysis stays in one operator's chat instead of becoming team knowledge,
- duplicate documents accumulate across wikis, issue trackers, PRs, and commit messages,
- in real project environments, the person who finds a problem cannot always change the code immediately; structured evidence helps the team discuss and decide.
Pindoc turns agent work worth keeping into searchable, code-pinned team memory. The next teammate or coding agent can ask Pindoc what matters before it edits.
What Makes Pindoc Different
- Collaborative memory layer: artifacts are written for teammates and future agents, not as private chat summaries.
- Agent-only write surface: the Reader UI is for reading and review; durable writes go through agents.
- MCP-native workflow: tools such as
pindoc.context_for_task,pindoc.artifact.propose, andpindoc.task.queueregulate agent behavior instead of acting as a thin CRUD API. - Typed artifacts: Decision, Analysis, Debug, Flow, Task, TC, Glossary, and domain-pack types.
- Code-pinned memory: artifacts can point to commits, files, line ranges, resources, URLs, and related artifacts.
- Record-worthy by design: Pindoc avoids raw chat archives and keeps only decisions, analyses, debug paths, verification, and task context with future value.
- Multi-project daemon: one
/mcpendpoint can serve multiple projects; each tool call carriesproject_slug. - Self-host first: Docker Compose brings up Postgres, pgvector, the Pindoc daemon, and the Reader SPA.
Public Demo
A read-only public demo is a follow-up track and is not part of this OSS
release. Until it ships, the README, docs/, and a
self-hosted clone are the primary proof. Operators who want to evaluate
Pindoc end-to-end run docker compose up -d --build and inspect their own
artifacts.
The follow-up demo plan stays in Public Demo Plan for when a hosted instance is appropriate.
Quick Start
Prerequisites:
- Docker 27+
- 2 CPU cores and 4 GB RAM recommended for local dogfood or small-team use
- 5 GB free disk recommended for Docker images, Postgres data, and the embedding cache; 2 GB is a light fresh-clone minimum
- outbound HTTPS on first run so the bundled EmbeddingGemma model and runtime can be cached
- Go 1.25+ only for host-native development
- Node 20.15+ and pnpm 10+ only for web development outside Docker
The default Docker path includes semantic search through a bundled EmbeddingGemma Q4 ONNX provider, so no embedding sidecar is required. See System Requirements for minimum and optional deployment profiles.
To make the running daemon report the exact source revision, pass the current commit through the Compose build argument before building:
PowerShell users can set the same value with
$env:PINDOC_BUILD_COMMIT = git rev-parse HEAD. make compose-up performs
this stamping automatically.
Open the Reader:
Check that the database ledger matches the migrations embedded in the image:
The command is read-only and exits non-zero for unknown applied migrations, pending migrations, or checksum drift. It never deletes or accepts an unknown schema change automatically.
Preview and repair semantic indexes that are unknown, stale, failed, or were built with a different embedding model:
Pindoc records the indexed revision, title/body hashes, model identity,
attempt count, and last error in artifact_index_state. Embeddings are fully
prepared before old chunks are replaced. If the provider fails, the artifact
write can still succeed with index_state.status="failed" and
retryable=true, while the last known-good chunks remain searchable. The
re-embed command handles each artifact in its own transaction and exits
non-zero if any retry still fails.
On a fresh instance, / first asks for the owner identity (display name and
email), then routes to the first-project wizard. To open the project wizard
directly after identity setup:
Repair Ownerless Projects From Older REST Builds
Older builds could create a project through POST /api/projects without a
matching project_members owner row. After upgrading, repair any affected
project by assigning the configured loopback owner:
Connect an MCP Client
The Docker daemon exposes one account-level MCP endpoint:
Project scope is not encoded in the URL. Agents pass project_slug on
project-scoped tool calls. Workspaces generated by pindoc.harness.install
store that slug in PINDOC.md frontmatter. pindoc.workspace.detect
resolves the likely slug for the current workspace, but it does not mutate the
daemon-wide PINDOC_PROJECT default. In a multi-project Docker daemon, keep
passing the detected project_slug explicitly after the session sweep.
completeness=draft is a maturity/trust state, not an unpublished private
draft. Accepted MCP writes are still published and Reader-visible when
visibility allows. Use visibility=private or the review workflow for content
that must not appear on the normal user surface.
Common Workflows
Ask an agent to start work with project context:
Typical MCP loop:
pindoc.workspace.detectpindoc.task.queuepindoc.context_for_task- code or doc work
pindoc.artifact.propose- update Task acceptance and closeout state
Asset uploads from Docker Desktop / Windows
pindoc.asset.upload(local_path=...) reads paths from the MCP server
host/container, not from the Windows client. For Docker Desktop, copy the host
file into the pindoc-server-daemon container first:
The script prints the JSON input for pindoc.asset.upload, including the
container-local /tmp/pindoc-asset-upload/... path.
For Reader-visible inline images, two steps are intentionally separate:
- Put
inbody_markdown; this controls rendering. - Call
pindoc.asset.attachwithrole="inline_image"; this records revision metadata and evidence.
Configuration
The default Docker path is single-user and loopback-only:
Do not expose a writable daemon to the public internet without an identity
provider. For a public read-only demo, keep /mcp and mutating HTTP routes
blocked at the reverse proxy; see SECURITY.md and
docs/22-public-demo.md.
The daemon also sets baseline security headers itself, including nosniff,
clickjacking protection, referrer policy, and hardened asset-blob CSP.
For a writable public or cross-device instance, follow
docs/oauth-setup.md. It covers GitHub OAuth App setup,
the ${PINDOC_PUBLIC_BASE_URL}/auth/github/callback callback rule, runtime
MCP client registration, and local OAuth QA with PINDOC_FORCE_OAUTH_LOCAL.
Development
To test the OAuth bearer path locally while still connecting through
127.0.0.1, set PINDOC_FORCE_OAUTH_LOCAL=true; the daemon will warn on boot
and require Bearer tokens for loopback /mcp calls.
On Windows hosts without a local C toolchain, run Go tests through Docker:
Run database integration tests against a disposable Postgres/pgvector database;
never point PINDOC_TEST_DATABASE_URL at a personal or production Pindoc
database. Test and plugin fixtures must opt into Reader isolation explicitly:
set projects.CreateProjectInput.ReaderHidden to true, or set
projects.reader_hidden = TRUE when inserting with SQL. Slug-prefix detection is
deprecated and no longer runs at request time. Migration 0070 only performs a
one-time backfill for fixture prefixes used by older Pindoc releases.
Documentation
- Documentation Hub
- Public Demo Plan
- Public Demo Story Path
- Record-worthy Artifact Policy
- Public Release Checklist
- Contributing
- Security
- Design source notes
Feedback
Long-form questions, feature requests, and design discussions go to GitHub Discussions. Bug reports go to GitHub Issues. The maintainer typically responds within a day.
Status
Pindoc is in active dogfood. The local self-host path, Reader UI, project/area model, artifact proposal flow, task queue, revision history, summaries, and real embedding provider path are implemented. The public OSS launch track is focused on first-run reliability, a read-only dogfood demo, CI, security docs, and clearer collaborative positioning.
License
Apache License 2.0. See LICENSE.
Source: README.md at commit 075f3c1
Tools
0Version history
1- v0.2.0LatestSep 16, 2026
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