Linear keeps your engineering team moving with structured issues, cycles, and milestones. Neo4j stores the relationships your flat tools miss - dependencies between services, ownership chains, historical impact patterns. Neotask bridges these two so your project data gains a third dimension. Ask questions like "which teams are blocked by this issue?" or "what past issues does this new bug resemble?" and get answers drawn from your graph database without leaving your workflow. Instead of copying issue IDs into Cypher queries by hand, Neotask handles the translation, letting engineers and project leads treat their graph database as a live intelligence layer on top of Linear.
Visualize how Linear issues connect across teams and services.
Query relationships between tasks, bugs, and systems in Neo4j.
Trace issue chains faster using connected graph data.
Map Issue Dependencies as Graph Relationships Create or update nodes in Neo4j whenever a Linear issue changes state. Build a living dependency graph that reflects your actual project topology - not just the parent/child links Linear exposes natively.
Query Impact Before You Ship Before closing a milestone or merging a fix, run a Cypher traversal to find all related nodes - downstream services, blocked issues, affected teams. Neotask surfaces that graph query result alongside your Linear cycle progress.
Enrich Issues with Graph Context Search Neo4j for nodes matching an issue's labels, component, or assignee, then attach the results as a comment or description update in Linear. Your issues carry the institutional knowledge your graph holds.
Track Team Velocity Through Graph Metrics Store sprint velocity data as time-series nodes in Neo4j. Query trends across multiple cycles and post summaries back to Linear projects or milestones automatically.
Identify Recurring Patterns in Issue History Run similarity queries in Neo4j against historical issue data. When a new Linear issue is created, flag it if it matches a known failure pattern - reducing duplicate root cause investigations.
Sync Label Taxonomies Across Both Systems Manage your label hierarchy in Neo4j as a graph of categories and subcategories. When labels change in Linear, reflect those updates in your graph schema to keep both systems consistent.
Neotask connects to both Linear and Neo4j through your account credentials. You describe what you want in plain language - for example, "find all Neo4j nodes related to the authentication service and create Linear issues for any that have no owner" - and Neotask breaks that into the right sequence of steps. It runs Cypher queries against your Neo4j instance, reads or writes Linear issues and projects using Linear's API, and combines the results into a coherent output. You can run one-off tasks or set up repeatable workflows triggered by issue state changes, label additions, or cycle completions. No custom scripts or API glue code required - Neotask handles the orchestration so your team focuses on the work itself.
| Capability | Linear | Neo4j |
|---|---|---|
| Create Linear issues from Neo4j query results | true | true |
| Run Cypher queries using Linear issue fields as parameters | true | true |
| Map Linear projects and milestones as graph nodes | true | true |
| Search Linear issues by label, assignee, or cycle | true | false |
| Explore Neo4j schema and relationship types | false | true |
| Update issue descriptions with graph query output | true | true |
| Track cycle velocity as time-series graph data | true | true |
| Detect duplicate or recurring issues via graph similarity | true | true |
Use descriptive node labels in Neo4j that mirror your Linear label taxonomy - this makes cross-system queries far more intuitive when you describe tasks to Neotask.
Store Linear issue IDs as properties on your Neo4j nodes. This lets Neotask look up and update the right Linear record when traversing your graph without ambiguity.
When exploring a new dependency chain, ask Neotask to summarize the graph output in plain language before taking any action in Linear - this gives you a chance to review before issues are created or updated.
Yes, Neotask connects to your Neo4j instance using the credentials you provide. It supports both Neo4j Aura cloud instances and self-hosted deployments accessible over the network. Your credentials are stored securely and never shared.
Neotask can both read from and write to Neo4j. It can create nodes, update properties, add relationships, and run any Cypher statement your account has permission to execute. You can review what Neotask plans to write before it runs if you prefer a confirmation step.
Neotask supports the full range of Linear operations including creating and updating issues, searching by label or assignee, managing projects and milestones, tracking cycle progress, updating team velocity metrics, and managing labels. If Linear exposes it via their API, Neotask can work with it.
Yes. By storing historical issue data in Neo4j with relevant properties - component, error type, affected service - you can ask Neotask to run a similarity query whenever a new Linear issue is created. If a match is found above a threshold you define, Neotask can comment on the new issue with the related historical context.
Absolutely. Neotask writes and runs Cypher queries on your behalf based on plain language instructions. You do not need to know graph query syntax. That said, having a well-structured Neo4j schema will produce more reliable and meaningful results, so it helps to define your node types and relationships with intention upfront.
Neotask connects Linear and Neo4j so your team can query relationships, track dependencies, and surface patterns - all from a single conversation.
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