Bunqueue
High-performance job queue for Bun with SQLite persistence, DLQ, and AI agent MCP support.
If you're building on Bun and need a production job queue without the overhead of Redis, Bunqueue is a compelling choice. Its MCP server for AI agent control is a unique differentiator. However, the SQLite-only persistence may not suit every deployment, and multi-language worker support is absent.
- Bun developers needing a production job queue without managing Redis
- AI agent builders who want to schedule and monitor tasks via MCP
- Serverless and edge compute applications (e.g., Cloudflare Workers)
- Teams migrating from BullMQ to a simpler, faster alternative
- Projects requiring a full message broker with publish/subscribe patterns (e.g., multi-topic fanout)
- Environments where Postgres/MySQL persistence is mandatory (SQLite only natively)
- Teams needing multi-language worker support (only TypeScript/JavaScript)
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In short
Bunqueue — High-performance job queue for Bun with SQLite persistence, DLQ, and AI agent MCP support. Best for Bun developers needing a production job queue without managing Redis, AI agent builders who want to schedule and monitor tasks via MCP, Serverless and edge compute applications (e.g., Cloudflare Workers). Free to use.
What's new in Bunqueue
Checked 14 days agoAcross the latest 9 updates: 9 changelog entries.
bunqueue 2.8.26: security fix, bug fixes for idempotent re-add, orphan jobs, workflow engine signal, moveToDelayed, dedup, metrics
Fixed idempotent re-add, orphan jobs collision, workflow double-execution, moveToDelayed silent no-op, dedup ignored in embedded mode, metrics always 0; SSRF guard blocks IPv4-mapped/compatible IPv6 and private IPv6 ranges.
bunqueue 2.8.25: fixed finishedOn/processedOn undefined in list queries
finishedOn/processedOn always undefined on jobs from list queries fixed (#104).
bunqueue 2.8.24: TCP frame parser linear performance, fewer copies, docs benchmarks re-measured
TCP frame parser made linear O(F²) → O(F) under pipelining; fewer copies and removed O(Q²) background scan; docs benchmarks re-measured.
bunqueue 2.8.23: FlowProducer audit fixes cross-queue parent linkage and addBulkThen result access
FlowProducer audit fixed two real defects: cross-queue parent linkage and addBulkThen result access.
bunqueue 2.8.21: addBulk up to 32× faster over TCP with O(n²) hot paths removed
Eliminated two O(n²) hot paths in batch push; addBulk up to 32× faster over TCP.
bunqueue 2.8.22: cancel/removeAsync did not remove flow-chain jobs in waitingDeps
cancel()/removeAsync() did not remove flow-chain jobs parked in waitingDeps (#102).
bunqueue 2.8.19 and 2.8.20: lock expiry fix, completion loss fix, queue control-state persistence fix
2.8.19: fixed completion loss when lock expired mid-processing & queue control-state not persisted. 2.8.20: fixed embedded job.remove/removeAsync not awaiting cancellation.
bunqueue 2.8.18: Worker over-pulled jobs past concurrency fixed
Worker over-pulled (leased) jobs past concurrency (#98; RED→GREEN reproduction).
bunqueue 2.8.15-2.8.17: multiple bug fixes for retry, stale-ACK, lock expiry
Fixed retry of lock-expiry failure (unique constraint), stale-ACK timeout resurrection, and two other defects from destruction-validation audit.
Viability Score
How likely is Bunqueue to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Zero external dependencies (SQLite WAL mode)
- 150K+ ops/sec with <1ms p99 latency
- Dead letter queues for failed job inspection
- Cron scheduling with timezone support
- S3 backup and disaster recovery
- Workflow engine with saga compensation, branching, sub-workflows
- Native MCP server (73 tools) for AI agent control
- Drop-in BullMQ compatible API
- Rate limiting and concurrency control
- Stall detection and lock-based worker ownership
- Sharded priority queues for multi-core scaling
- Embedded (in-process) and TCP server deployment modes
- Retries with backoff
- Delayed jobs and repeatable tasks
- Prometheus metrics endpoint
About Bunqueue
Bunqueue is a job queue library built specifically for the Bun runtime, offering a full-featured queue system with SQLite persistence (WAL mode), zero external infrastructure dependencies (no Redis or RabbitMQ), and sub-millisecond latency. It is designed for production workloads including AI agent automation, microservices, and serverless applications. The library ships with a familiar Queue/Worker API (drop-in BullMQ replacement), built-in dead letter queues, rate limiting, retries with backoff, cron scheduling, S3 backups, and a workflow engine for orchestrating multi-step processes. It also includes a native MCP (Model Context Protocol) server with 73 tools, enabling AI agents like Claude or Cursor to schedule and manage jobs via natural language. Bunqueue runs in two modes: embedded (in-process, zero network overhead) or as a standalone TCP server for distributed workers. It achieves over 150K ops/sec with <1ms p99 latency and minimal memory usage (~50MB). Unlike alternatives like BullMQ or BullMQ Pro, Bunqueue eliminates the need for Redis entirely, dramatically reducing operational complexity while delivering superior performance and an integrated MCP server for AI agent workflows.
Behind the Verdict
Bunqueue stands out by delivering a fully featured job queue that runs entirely on Bun's native SQLite, with no need for Redis or any other external service. This simplicity is a huge win for teams who want to deploy a queue without managing extra infrastructure. The performance is impressive — 150K+ ops/sec with sub-millisecond p99 latency — and the API feels familiar to anyone who has used BullMQ, making migration straightforward. The built-in MCP server is genuinely novel: AI agents can schedule and monitor jobs via natural language, which is a forward-looking move given the rise of agentic workflows. You get a dead letter queue, cron scheduling, S3 backups, rate limiting, and a workflow engine with saga compensation and sub-workflows — all without third-party services. Where Bunqueue may fall short is its reliance on SQLite; if your organization mandates Postgres or MySQL, this tool isn't compatible (at least natively). Also, workers are limited to TypeScript/JavaScript — no Python, Go, or Rust support unless you wrap them. The development pace is active, with frequent bug fixes and performance improvements (latest version 2.8.26 as of July 2026). For Bun projects, especially those involving AI agents or serverless, Bunqueue is the best queue option we've seen. Compared to BullMQ Pro, it's free and open source, but lacks native pub/sub beyond the queue pattern.
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Use Cases
- Schedule email digests with cron and retry logic for failed sends.
- Orchestrate multi-step data pipelines with compensation on failure.
- Let an AI agent spin up batch processing jobs via natural language MCP commands.
- Process webhook payloads with rate limiting and priority queues.
- Offload CPU-intensive image processing tasks from HTTP handlers.
- Build a serverless automation system that runs jobs from a single file.
Limitations
- Bunqueue uses SQLite for persistence, which is not suitable for multi-writer distributed scenarios out of the box (TCP server mode supports multiple clients but still uses a single SQLite file).
- It does not include native transactional outbox patterns or cloud-provider-specific integrations.
- The workflow engine is TypeScript-only.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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