sprinter
A self-hosted backlog tracker with priority scoring and an MCP server, enabling AI agents to autonomously pull, work on, and update tasks via JSON-RPC tools.
README
⚡ sprinter
A self-hosted, gated work-backlog tracker with priority scoring, a filterable/sortable UI, and a built-in MCP server — so AI agents can pull the next item, do the work, and report progress back.
sprinter was built to drive an autonomous remediation loop: a fleet of agents queries the backlog over MCP (next_item), implements a fix, and marks the item done (update_item) — every change audit-logged. It works just as well as a plain human backlog board.
<!-- Add screenshots here: docs/backlog.png, docs/board.png -->
Why it exists
Most issue trackers are built for humans clicking around. sprinter is built so an agent can:
loop:
item = mcp.next_item(category="security") # highest-priority open item
patch = implement_fix(item)
mcp.update_item(item.id, status="fixed", notes="patch at ...")
…while a human watches the same data in a clean web UI (filter, sort, board, drill-down) and the database stays the single source of truth.
Features
- Priority scoring — every item carries Urgency / Impact / Effort (1–10); priority =
U×I/E, so cheap-but-valuable work floats to the top. Re-scoring recomputes automatically. - Filter & sort everything — by app, category, severity, status, free-text search, priority/effort ranges; server-side pagination (
LIMIT/OFFSET+ count) keeps it fast on thousands of items. - Board view — kanban by status (
open → in_progress → fixed → done). - Apps registry — track items against the apps/repos they belong to (URL, repo path, stack, LOC, open/critical/high counts).
- Systemic themes — roll up issues that recur across many apps into portfolio-level initiatives.
- MCP server — 9 tools (
list_apps,query_items,get_item,next_item,update_item,add_item,list_themes,stats,get_app) over JSON-RPC; bearer-token gated. Point any MCP client at it. - Gated by default — the whole app sits behind a login (scrypt + HMAC-signed session cookie, login rate-limiting); the MCP endpoint requires a bearer token. Nothing renders pre-auth.
- Change log — every status/score/notes mutation is recorded with actor + timestamp.
Stack
FastAPI · PostgreSQL (any PG-wire-compatible engine works) · vanilla-JS single-page UI (no build step) · a dependency-light MCP JSON-RPC server. One small container + a database.
Quickstart
git clone https://github.com/danimoya/sprinter && cd sprinter
cp .env.example .env
# set DB_PASSWORD, SPRINTER_PASSWORD, SPRINTER_SESSION_SECRET (openssl rand -hex 32),
# and SPRINTER_MCP_TOKEN if you want the MCP endpoint enabled
docker compose up -d --build
docker exec sprinter python ingest.py # loads the synthetic demo seed from ./demo
open http://localhost:8000 # log in with SPRINTER_USER / SPRINTER_PASSWORD
The repo ships a synthetic demo dataset (demo/) — fictional apps and findings — so it's useful the moment it's up. Replace it with your own apps.json / backlog.json / themes.json (same shape) and re-run ingest.py.
MCP
Enable by setting SPRINTER_MCP_TOKEN, then register the endpoint with any MCP client:
claude mcp add --transport http sprinter http://localhost:8000/mcp \
--header "Authorization: Bearer $SPRINTER_MCP_TOKEN"
next_item returns the single highest-priority open item — ideal as the head of an autonomous fix loop. update_item moves it through in_progress → fixed → done. All write tools require the token; reads do too.
Data model
- apps —
key, name, urls[], repo_dir, profile, stack[], datastores[], loc, open_items, critical, high, max_priority - items —
id (stable hash), app, category (security|dast|infra|stub|improvement|feature), title, description, severity, cwe, owasp, location, evidence, remediation, confidence, urgency, impact, effort, priority, status, assignee, notes, … - themes — cross-cutting initiatives spanning ≥3 apps
- change_log — audit trail of every mutation
Status lifecycle: open → in_progress → fixed (work done, pending deploy) → done (live), plus wontfix and rejected.
Security notes
- Set strong values for
SPRINTER_PASSWORD,SPRINTER_SESSION_SECRET, andSPRINTER_MCP_TOKEN. With no password set, login is disabled (fail-closed). With no MCP token, the MCP endpoint returns 401. - Put it behind a TLS-terminating reverse proxy in production and drop the
ports:mapping (proxy by container name). - The schema deliberately avoids
UNIQUE-on-TEXT; idempotency is handled iningest.py(full refresh) andupdate_item(by id).
License
MIT © Daniel Moya — see LICENSE.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.