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Sprintra vs claude-mem

Two open-source approaches to giving AI coding agents persistent project context. claude-mem is a memory plugin. Sprintra is a project workspace with memory built in. This page is an honest, side-by-side comparison.

TL;DR

  • Pick claude-mem if you only need session memory inside Claude Code, you're a solo dev, you don't mind AGPL, and you're willing to pay LLM cost on every tool call to compress observations.
  • Pick Sprintra if you also want sprints, decisions, knowledge base, dependency graph, multi-agent support, team mode, hosted SaaS, MIT license, and zero per-tool-call cost.
  • Use both? They don't conflict at the file level, but most users settle on one — Sprintra includes the memory layer claude-mem provides.

Scope

Feature

Sprintra

claude-mem

Persistent session memory
Yes

Prompts + agent-written digests + transcript index

Yes

Tool-call observations compressed into vector store

Project management (sprints, features, stories)
Yes
No

Memory only

Architecture decision records (ADRs)
Yes

With conflict detection

No
Knowledge base + cross-linking
Yes
No
Dependency graph
Yes
No
Releases + auto release notes
Yes
No

Capture

Feature

Sprintra

claude-mem

Per-observation cost
Zero LLM cost

Agent writes digests in-context using free reasoning

LLM call per observation

ChromaDB embedding + AI compression on every tool call

Background reorganization (Auto Dream-style)
Yes

Stop hook triggers digest write

Yes

Periodic compression + clustering

User prompt timeline
Yes

Per-user, private by default

Partial

Captured as part of observations

Local transcript search
Yes

FTS5 over Claude Code's existing JSONL

Yes

Vector + keyword search

Distribution + license

Feature

Sprintra

claude-mem

License
MIT

Permissive; no procurement blockers

AGPL-3.0

+ PolyForm Noncommercial subdirectory; AGPL is a procurement blocker for many enterprises

GitHub stars
Growing

Solo-built, MCP-first

71k+

Mindshare leader in memory category

Hosted SaaS
Yes

app.sprintra.io

No

Self-host only

Tokenomics / cryptocurrency
No
$CMEM Solana token

Officially embraced by maintainer

Multi-agent + multi-user

Feature

Sprintra

claude-mem

Cross-IDE support
Yes

Claude Code, Cursor, Codex, Antigravity, Gemini CLI — uniform via MCP

Partial

Claude Code primary; Gemini CLI / OpenClaw bolt-on

Team mode (multiple users in one project)
Yes

Per-user privacy + shared project artifacts

No

Single-user local

RBAC + custom roles
Yes

8-step permission cascade

No
Multi-org tenant isolation
Yes

Hard org boundary, fail-safe org resolution

No

Visibility

Feature

Sprintra

claude-mem

Visual dashboard
Yes

Kanban, sprints, roadmap, dependencies, KB graph — 20+ views

Partial

Static memory archive site

Real-time activity feed
Yes

SSE-driven

No
Decision conflict detection
Yes

Semantic comparison via embeddings

No
Audit trail / activity log
Yes
Partial

Memory archive only

Where Sprintra wins

  • Full project workspace — sprints, features, decisions, KB, deps, releases
  • Zero LLM cost capture — your token budget stays for the actual work
  • Team mode + per-user privacy + RBAC + multi-org
  • Cross-IDE — same memory readable by Claude Code, Cursor, Codex, Antigravity, Gemini CLI
  • Visual dashboard with kanban, roadmap, KB graph (not just memory archive)
  • MIT license — no AGPL procurement blockers

Where claude-mem wins

  • Larger GitHub mindshare — first thing devs find when searching 'Claude Code memory'
  • Pure-play simplicity — easier to explain in one sentence
  • First-mover habit — many users already wired in
  • Simpler scope — no PM concepts to learn if you only want memory

Our honest take

claude-mem solved memory. We're solving project context.

Memory alone is the floor. The actual problem is that AI agents lose project context — what was decided, what's blocking, what's in the current sprint, what depends on what. That's what Sprintra exists for. We treat memory as a layer beneath the project workspace, which is why our capture is zero LLM cost: the agent that's already in your context writes the digest, no extra inference round-trip.

Try Sprintra

Free open-source MCP server. Local SQLite or hosted SaaS. 30-second install.

Install in 30 secondsView on GitHub