AI said it finished. Flyto2 shows the proof.

Verified generative visualization for React and agents, with deterministic chart validation, repair, rendering evidence, and MCP.

Local codebase intelligence CLI + MCP server for AI coding agents: SQLite code graph, 28 languages, 287 commands, 246 MCP tools, change-safety gates, audit evidence, zero API keys.

Enables capturing a tamper-evident, hash-chained local record of every AI agent tool call — both the decision before a tool runs and its outcome — so you can review what the agent actually did in order, detect edits, deletions, or reordering at the exact index, and export a signed evidence pack any third party can verify with no installs.

Enables AI agents to load web pages in true-to-size iPhone, iPad, and Android device frames, capture screenshots, inspect interactive elements and layout diagnostics, and automate tap/type/scroll flows with network mocks, console errors, and test evidence.

Read-only checks for money that agents move. verify_receipt: schema, Ed25519 signature, mandate expiry, amount = quantity x unit_price, refund not above payment. audit_spend: duplicate charges, price escalation, failed-but-billed, runaway loops, missing refunds, model overpay, budget breaches - three separate amounts, never one. reserve_report: NAV with an evidence hash per line; refuses a backing

Enables AI agents to search 1,900+ exercises with video and media links, generate workouts and multi-week programs, explore evidence-rated supplements, and use developer tools for API modeling, debugging, and usage insights.

Product context for AI agents: evidence, opportunities, initiatives, and decisions.

Reverse-engineering tools for agents over MCP/A2A, with evidence-carrying findings.

Agentic Version Control System — an AI-native VCS where intent, session, operation, evidence and decision are first-class objects and code is a materialized projection of an operation graph.

Enables agents to inspect React Native and Expo apps through React's runtime tree, identify source locations, act on elements without coordinates, and verify outcomes with assertions and runtime evidence.

AI agent identity, signed credentials, delegated authority and portable governance evidence. Python core and offline verifier SDKs.

Re-debugging Solved Failures? No Way. 500+ Evidence-graded fix lessons, One MCP Call-->https://misakanet.org

LeanCTX is the Context Gateway for AI Systems. Select task-relevant context, apply supported controls, connect local knowledge and inspect recorded evidence. Open-source Engine: CLI, MCP, hooks and supported proxy paths.

Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.

Project memory and workflows for Claude Code and Codex. Keep stories, plans, handovers, and review evidence in your repo. Resume across sessions and follow progress in the Mac app.

Audit AI applications and agents for security risks before commit, PR, merge, or deployment. Deterministic findings with coverage and evidence receipts.

Enables AI agents to drive policy evaluation over MCP by starting executions, answering policy questions from case evidence, and reading deterministic outcomes with reasoning traces, while the runtime controls which questions are asked and how answers combine.

Enables coding agents to propose, review, promote, and verify architecture changes as recorded C4 model updates, with hypothetical diffs, evidence-based qualification, and component histories.

Enables agents to probe URLs and classify bot-wall responses with vendor and signal evidence, perform offline classification, scan for exposed key-like material, and run owner-side access audits through stdio tools.

Enables AI agents to query Korean public data from OpenDART, data.go.kr and law.go.kr — corporate filings and financials, stock prices, apartment trades, business registration status, holidays, statutes in force on a given date, and court rulings. It corrects the live APIs' known traps (mislabeled periods, not-yet-in-force laws, cancelled trades, changed district codes) so answers come back right, with evidence.

Enables LLM-powered developer environments to discover and evaluate potentially beginner-friendly GitHub issues using explainable heuristics, clear rationale, and direct evidence links over stdio.

A read-only server that enables AI agents to triage Kubernetes CronJobs in a single tool call: whether runs happened and stayed on schedule, whether durations are trending slower or overrunning, which jobs have silently stopped succeeding, and why a given run failed, with evidence and stated basis for each verdict. It also lists active runs and recent failures while enforcing namespace allowlists and no write access.

Enables agents to ingest local registry snapshots, detect removed or newly deprecated tools and schema-breaking changes, verify deprecation claims against hash-chained evidence, and generate migration diffs for agent configurations.