Tracecat vs Tines: Which is best for you?

Tracecat includes a dedicated AI agent builder, skills registry, subagents, and sandboxed execution. Tracecat agents are designed to operate as long-running AI colleagues that can investigate, reason, and take action across tools.

Tines supports AI agents inside workflows, but its agent model is centered around workflow steps. That works well when an agent is one part of a larger deterministic process. Tracecat is better suited when agents are the primary interface for investigation, enrichment, decision-making, and response.

Tracecat’s MCP server is purpose-built for Claude Code, Microsoft Copilot, and other coding assistants. The goal is simple: every important Tracecat capability should be available to the tools security engineers already use to write code, review logic, generate integrations, and debug automations.

Tines also supports MCP, but its product center of gravity remains the visual storyboard. Tracecat’s center of gravity is different: the platform is designed so builders can move between UI, code, agents, MCP, and version control without changing how they think about the system.

Tracecat includes 500+ integrations and 50+ security-specific MCP servers that agents can use directly or inside workflows. These MCP servers can be remote or stdio-based, which gives teams more flexibility when connecting local tools, internal systems, and security engineering workflows.

Tines supports connecting AI agent actions to remote MCP servers, which is useful for workflow augmentation. Tracecat goes further by treating MCP servers as a native tool layer for both standalone agents and orchestrated workflows.

Tracecat lets teams bring their own Python functions and template integrations from git with a single click. Once registered, those functions can be reused globally across workflows and agents. This makes integrations easier to maintain, easier to review, and easier to improve over time.

Tines supports Python through workflow actions and custom runtimes. That is useful when a workflow needs script execution, but Tracecat is designed around reusable engineering assets: shared functions, git-backed registries, and code that can be used across the platform.

Tracecat syncs workflows, agents, and table schemas to your existing version control system, including GitHub, GitLab, and Bitbucket. This lets security teams use the same review, rollback, branching, and change-management practices they already use for infrastructure and application code.

Tines has its own versioning experience for workflows inside the product. That is helpful for visual workflow management, but it does not replace external version control for teams that want security automation to live alongside the rest of their engineering assets.

Tracecat gives teams unlimited workflows, so they can build smaller, modular automations that are easier to maintain. Instead of forcing teams to pack more logic into fewer workflows, Tracecat encourages workflow-as-function design: smaller units, clearer ownership, and better reuse.

Tines pricing and packaging is more modular. Depending on the plan, teams may need to account for flows, events, cases, AI usage, API access, version control, or other packaged capabilities. Tracecat is designed around all-in-one pricing for teams that want to build broadly without worrying that every new automation creates another pricing decision.

Tracecat is open source. Users can inspect the platform code, review integration logic, contribute improvements, and avoid being locked into a black-box automation system. This also makes Tracecat easier to pair with coding assistants, because the assistant can reason over real platform and integration code.

Tines is closed source and proprietary. It has excellent documentation and support, but customers do not have the same ability to inspect, modify, or contribute to the underlying platform and integration code.

Tracecat’s founders and engineers work directly with customers to build agents, ship integrations, and improve the product. Customers help shape the roadmap, especially as Tracecat pushes deeper into AI-native security operations.

Tines has strong customer support, technical account management, and customer success. Tracecat’s difference is that support is closer to the people building the product.