Figural provides an intermediary layer that keeps AI coding agents aligned with developer specifications by automatically extracting project constraints from code, documentation, and team communications and injecting them into agent sessions via the Model Control Protocol. It monitors agent actions in real time, flags any deviations with precise location details, and offers one‑click re‑injection to restore correct behavior, while logging all decisions for auditability.
Funding
Funding not disclosed
Founders
Product
Problem
AI coding agents can lose alignment with developer intent over time, especially during long sessions or when multiple tools and decisions are involved, leading to unintended code changes, violations of project constraints, and loss of context.
Solution
Figural acts as an intermediary layer that continuously synchronizes AI agents with the developer’s specifications and project constraints. It automatically extracts relevant information from the codebase, documentation, and team communications, injecting this context into agent sessions via the Model Control Protocol (MCP). As the session progresses, Figural re‑injects the specifications to prevent context loss and monitors agent actions for any deviation from agreed decisions, flagging violations with precise file, line, and rationale details. When a drift is detected, a single click restores the correct spec, keeping the agent on track. All decisions, drifts, and spec updates are logged in a version‑controlled file within the repository, providing a permanent audit trail.
Target Audience
Figural is intended for development teams that use AI coding agents to automate code generation and need reliable alignment with project specifications and constraints.
Features
- Automatic extraction of specifications from code, docs, and team conversations
- Real‑time injection and re‑injection of specs into any MCP‑compatible AI coding agent
- Immediate detection and flagging of constraint violations with exact location and reason
- One‑click re‑injection to correct agent behavior without manual prompting
- Agent‑agnostic design that works with any AI coding tool supporting MCP
- Persistent decision log (.figular/decisions.log) committed alongside source code for traceability