Mattermost
Mattermost v11.11 adds data spillage exposure tracking as v12.0 breaking changes loom
A side-by-side editorial comparison of Joplin and Novelcrafter — release velocity, themes, recent moves, and the top alternatives to consider.
Joplin 3.7 ships AI chat, semantic search, and MCP integration — all off by default, all controllable by the user.
Joplin 3.7 is the product's first real AI release: an in-app chat panel for querying the currently open note, semantic (meaning-based) search across notebooks, and an MCP server that lets external AI assistants connect to Joplin's note graph. The implementation is privacy-first by design — AI is disabled by default, local models (Ollama, LM Studio) are explicitly supported, and cloud AI services only receive the specific note content relevant to a request rather than the full notebook. A companion documentation post published September 14 lays out the privacy model explicitly.
Novelcrafter keeps the model layer swappable and spends its own effort on the manuscript instead.
Two threads run through this window. The first is model plumbing: default collections refreshed as Claude 4.5 Sonnet, Gemini 3 Pro, and GPT-5.1 arrive, a generic OpenAI-compatible provider so unsupported vendors work anyway, and an opt-in control to prefer or avoid reasoning across Scene Beats and Chats. The second is the writer's own data — Codex entries can be marked case-sensitive so a character named Will stops matching every sentence, and an entry can sit in several custom categories at once. Word export gained bullet and numbered lists. The feed stops in March 2026.
Joplin 3.7 is the product's first real AI release: an in-app chat panel for querying the currently open note, semantic (meaning-based) search across notebooks, and an MCP server that lets external AI assistants connect to Joplin's note graph. The implementation is privacy-first by design — AI is disabled by default, local models (Ollama, LM Studio) are explicitly supported, and cloud AI services only receive the specific note content relevant to a request rather than the full notebook. A companion documentation post published September 14 lays out the privacy model explicitly.
Joplin is repositioning from a sync-agnostic note-taking app into an AI-native knowledge base, differentiated by opt-in, local-first controls. The HMD Terra M preload partnership and the warrant canary point to a deliberate push toward privacy-conscious enterprise and professional users who distrust cloud-first tools. The MCP integration is particularly strategic: it makes Joplin's note graph accessible to external orchestration pipelines without locking into any particular AI provider.
The next major release will likely expand AI chat to multi-note context — currently limited to the open note — and add more configurable MCP tools. The HTR (handwritten text recognition) project from the 2024 French government partnership is also likely to appear in a near-term release.
Two threads run through this window. The first is model plumbing: default collections refreshed as Claude 4.5 Sonnet, Gemini 3 Pro, and GPT-5.1 arrive, a generic OpenAI-compatible provider so unsupported vendors work anyway, and an opt-in control to prefer or avoid reasoning across Scene Beats and Chats. The second is the writer's own data — Codex entries can be marked case-sensitive so a character named Will stops matching every sentence, and an entry can sit in several custom categories at once. Word export gained bullet and numbered lists. The feed stops in March 2026.
The model layer is treated as commodity and kept deliberately replaceable: users can clone collections, revert to previous ones, or point at any OpenAI-compatible endpoint, and the reasoning control is a preference rather than a hardcoded behavior. Novelcrafter's own investment goes into the Codex — the structured record of characters, places, and rules that gets fed to whichever model is in play — and into getting manuscripts out cleanly. That is a defensible split for a tool whose value is the writer's accumulated context rather than the generation itself.
Expect further Codex precision work, since case-sensitivity and multi-category membership are both fixes for the same failure — the wrong entries being pulled into context. What the entries do not show is whether the experimental reasoning support graduates out of the settings flag.
Other Collab products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Joplin or Novelcrafter.
Mattermost v11.11 adds data spillage exposure tracking as v12.0 breaking changes loom
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See all Joplin alternatives → · See all Novelcrafter alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Joplin is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Joplin is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Collab products to evaluate alongside.
Top Joplin alternatives in Collab are ranked by recent ship velocity. Browse the "Joplin alternatives" section above for the current picks, or visit /alternatives/joplin for the full list with editorial commentary on each.
Top Novelcrafter alternatives in Collab are ranked by recent ship velocity. Browse the "Novelcrafter alternatives" section above for the current picks, or visit /alternatives/novelcrafter for the full list with editorial commentary on each.