What Spiderbrain is, how the context graph works, what stays on your machine, and what each plan costs. Plain, factual answers.
Spiderbrain is a context-engineering tool that builds a living context graph of your project and serves it to AI agents over the Model Context Protocol (MCP). Instead of pasting files into a chat, your agent gets persistent memory and structural reasoning: it understands how every file, function and decision connects, and what breaks when one of them changes. It runs on your machine and is free to start.
The product is written as one word, Spiderbrain. It is often searched as two words, Spider Brain, and both refer to the same tool at spiderbrain.ai.
It gives agents memory that persists across sessions, ranks the files that actually matter, and answers what a change will break before you ship it. The map updates itself as you work, and it plugs into Claude, Cursor and any other MCP client.
Yes. Spiderbrain includes a brain-aware agentic chat: you converse with an AI that retrieves your codebase context ranked by importance and shows a blast-radius warning before it makes any edit. It is multi-provider (Anthropic, OpenAI, Google, or local models via Ollama and LM Studio) and bring-your-own-key.
Context engineering is the practice of assembling the right information, memory and tools around an AI model so it can reason reliably. It is widely seen as the successor to prompt engineering: rather than wording a single message well, you engineer the whole context the model works from. Spiderbrain is a context-engineering based persistent cognition tool, built initially as a context graph that also reasons over what it stores.
A context graph is a structured map of how the parts of a project connect and depend on one another, instead of a flat pile of text. Gartner expects most AI-agent systems to use context graphs by 2028. Spiderbrain builds one automatically and goes further: it ranks what matters most and traces what fails when something changes.
RAG and vector databases retrieve chunks of text that look similar to your query. They have no sense of structure, so they cannot tell you what depends on what, or what breaks downstream. Spiderbrain keeps a structural graph and reasons over it, scoring every node by importance and tracing failure across dependencies. Most tools hand your agent a subway map. Spiderbrain hands it the same map with the broken tracks circled in red.
Not quite. A knowledge graph stores facts and relationships you define up front. Spiderbrain builds its graph automatically from your real files, imports and decisions, keeps it current as you work, and scores each node by how much its failure would hurt and how far that failure would spread. It is a context graph that ranks and reasons, not just a store of facts.
Context rot is the well-documented drop in accuracy as you push more text into a model’s context window. Flat dumps and stale embeddings make it worse, because the model spends attention on noise. Spiderbrain works on the input side: it ranks every part of your project by importance and blast radius, so your agent sees the load-bearing context first and the noise last.
Spiderbrain reads JavaScript, TypeScript, Python, Go, Java and C at the structural level, and handles other languages with a lighter parser. Beyond code it ingests Markdown, SQL schemas, PDF, docx, HTML, CSV and chat exports from ChatGPT, Claude and WhatsApp. It builds one graph across all of it, so your docs and decisions sit next to the code they describe.
Spiderbrain is MCP-native, so it connects to any client that speaks the Model Context Protocol. That includes Claude and Claude Code, Cursor, Continue, Cody, Zed, Windsurf, Devin, opencode and Aider. There is no glue code to write: connect the server once and your agent inherits memory and reasoning that stay current.
In local mode the brain is built on your device from your own files, and your source code stays on-device. The only things that can leave are your sign-in identity and, if you allow it, content-free usage counts that never include your code. Cloud and team features are opt-in, for when you choose to share a brain with colleagues.
Yes. Importing a project, querying the graph and recording decisions all work fully offline. You only need a connection to link a remote AI client over MCP, or to use the optional cloud and team features.
Spiderbrain is deterministic: the same input produces the same brain every time, with no randomness and no hidden model in the scoring path. The engine ships with a 30-gate test suite of 353 checks, all passing, and has been validated on real codebases. Anything an AI suggests is clearly labelled and never applied on its own, so you always know what is fact and what is a suggestion.
The graph updates itself as you work, so there are no stale embeddings to rebuild by hand. Drift detection flags files that have changed in ways that no longer match their history. On paid plans, a continuous live-watch re-scores your project automatically as it changes, so the picture is never behind.
Spiderbrain ships as a desktop app for macOS, Windows and Linux, alongside a headless command-line tool for CI and scripting and a native MCP server for editors. macOS 12 or later and Windows 10 or later are supported.
Every decision is recorded in an append-only log that is signed and hash-chained, so tampering is detectable and you can replay exactly how the brain reached its current state. Nothing is silently overwritten. For teams, that same log makes a shared brain auditable rather than a black box.
Plenty of tools can build a graph of your project. Far fewer can tell you which parts are load-bearing. Spiderbrain scores every node by how much it matters and how far its failure would spread, then keeps those scores current as you work. That ranking is the moat, and the paid plans sharpen it.
For small and medium projects, on your machine.
No credit card required.
Founding members pay $21/mo forever
For as long as you keep the plan. Until Spiderbrain Cortex General Availability or the first 500 members, whichever comes first.
Become one of the first developers helping define persistent cognition for AI infrastructure.
Upgrade from inside the app.
For teams that share one brain.
Sales-assisted onboarding.
For rollouts with specific needs.
Custom licensing and rollout.
Yes. The Local plan is free, with no credit card required. You get one project, the full on-device brain and MCP access. It is free for personal, research and open-source use, and it is the fastest way to see the difference on your own code.
Local is free and covers one project, entirely on your machine, and suits small and medium projects. Pro is $36 a month, and Founding Members lock in $21 a month for as long as they keep the plan; it raises you to five projects and adds the real upgrade: a continuous live-watch that re-scores your project automatically, plus cloud save and dedicated support tickets through Webby. Cortex, at $99 per seat each month, gives a team one deterministic shared brain with assisted merging and on-call support. Enterprise adds licensing, a custom rollout from Perform Digital, priority support and a dedicated account manager.
Spiderbrain Pro is $36 a month. Founding Members lock in $21 a month for as long as they keep the plan. The offer runs until Spiderbrain Cortex reaches general availability, or until the first 500 members join, whichever comes first. It is for the early developers helping define persistent cognition for AI infrastructure.
No. Download the free Local plan and build your first brain in minutes. When you are ready for live-watch, more projects or a shared team brain, you can upgrade from inside the app.
The headline is continuous live-watch. On the free plan you re-score when you choose to; on Pro, Spiderbrain watches your project and keeps the scores current automatically as you work, so your agent never reasons from a stale picture. Pro also lifts the limit to five projects, lets you save brains to the cloud, and gives you dedicated support tickets through Webby.
Yes, on the Cortex plan. Several people work against one deterministic shared brain, and Spiderbrain merges everyone’s view predictably, surfacing conflicts rather than guessing. Assisted AI merging is available as a labelled beta. For larger rollouts, Enterprise adds licensing and hands-on implementation.
Spiderbrain is built by Perform Digital, a team scaling SaaS since 2019 that builds specialized AI agents for B2B, alongside consulting, training and deep AI research into agent memory and reducing hallucination. The Spiderbrain algorithm is authored and engineered by Abhishek Srivastava, principal at Perform Digital. The engine is proprietary and is not on GitHub today; you can use it free on the Local plan, and commercial use is covered by the Cortex and Enterprise plans.
Webby, the assistant in the corner of this page, can answer product questions and, for customers on a paid plan, open a support ticket for you. Support tickets are available to paid members only. You can also email contact@perform.digital any time. For Cortex and Enterprise, you get a direct line to the Perform Digital team.
Webby, in the corner of this page, answers in plain language and can open a support ticket for paid customers. Or just download Spiderbrain and try it on your own code.