Eliminating unbounded tool hangs, zombie process leaks, and context-window pollution during local LLM tool execution.

When autonomous agents (Claude Desktop, Cursor, Ollama/vLLM tool callers) invoke bash scripts, Python interpreters, or external utilities, standard execution wrappers lack low-level defensive isolation. A single hanging command deadlocks the entire agent process. Runaway stack traces dump megabytes of text that crash LLM context windows, and directory traversal escapes access sensitive keys.

Tool-Shield provides an offline, zero-dependency hardened execution sandbox for Python 3.10+:

🛡️ Process-Group Isolation & Two-Phase Escalation: Dedicated process trees escalate from SIGTERM to hard SIGKILL, ensuring hung network sockets and runaway worker threads are completely eradicated.

📦 Context-Window Protection (Middle Truncation): Enforces a strict 64 KB byte cap, cleanly preserving head and tail tokens while purging bloated middle loops.

🧹 ANSI & Terminal Sanitization: Regex purges color escapes, cursor codes, and encoding artifacts into clean UTF-8 text for LLM JSON parsers.

🔒 Jailed Path Confinement: Canonical path resolver intercepts directory traversal (../../) attempts before any file action is allowed.

📊 Microsecond Forensic Flight Log: Embedded SQLite audit database (sandbox_audit.db) records timestamps, exit codes, and latency traces.

📦 100% Python Stdlib: Zero external pip dependencies. Runs offline across Linux, macOS, and Windows.

💰 Pricing: $19 USD (One-time payment • Lifetime As-Is Commercial License)

🔗 Direct Checkout: https://whop.com/checkout/plan_mgzidlRzj4Pdq

📖 Technical Spec & Benchmarks: https://sparkgrin-labs.github.io/articles/tool-shield.html

Connecting local LLMs to live market feeds, MQL5 sockets, and robotics telemetry without dropping a single frame.

When local models (Ollama, vLLM, llama.cpp) spend 300ms to 3,000ms generating tokens, traditional single-threaded socket loops overflow OS network buffers. This causes dropped market ticks, half-open TCP hangs, and corrupted JSON packet fragmentation.

Agent-IPC decouples high-speed socket ingestion from slow model inference:

⚡ Non-Blocking Selectors Multiplexer: Concurrently ingests >10,000 frames/sec on loopback TCP.

📦 4-Byte Binary uint32 Framing: Length-prefixed framing permanently eliminates TCP fragmentation and json.loads() crashes.

🛡️ SQLite WAL Overflow Spooling: Bursts automatically spill to persistent SQLite WAL storage during heavy model inference, with zero packet loss.

🔍 Autonomous Keepalive Watchdog: Automatically reclaims dead connections without blocking inference threads.

📦 Zero Pip Dependencies: Pure Python 3.10+ stdlib. No RabbitMQ, Kafka, or pyzmq compilation headaches.

💰 Pricing: $49 USD (One-time payment • Lifetime As-Is Commercial License)

🔗 Direct Checkout: https://whop.com/checkout/plan_zKXkXhulUT5Gt

📖 Technical Spec & Benchmarks: https://sparkgrin-labs.github.io/articles/agent-ipc.html

Building uncrashable Model Context Protocol (MCP) servers for Claude Desktop and Cursor without the 15+ package dependency trap.

Official MCP SDKs require heavy asynchronous dependencies (anyio, starlette, httpx, pydantic) and brittle virtual environment paths in claude_desktop_config.json. A single rogue print() statement pollutes stdout and severs the client connection.

MCP-Core provides a production-hardened, zero-dependency MCP stdio runtime:

🛡️ StdoutShield Technology: Automatically captures rogue prints and redirects them safely to stderr, preserving JSON-RPC 2.0 framing purity.

⏱️ Thread-Pool Sandboxing: Strict timeout enforcement prevents runaway tool subprocesses from freezing the host IDE.

📜 Microsecond Flight Recorder: Embedded SQLite audit database logs every incoming JSON-RPC frame and latency trace.

📦 Zero Pip Packages: Runs on bare-metal Python 3.10+ across macOS, Windows, and Linux.

💰 Pricing: $29 USD (One-time payment • Lifetime As-Is Commercial License)

🔗 Direct Checkout: https://whop.com/checkout/plan_emRvsQaptAGXo

📖 Technical Spec & Benchmarks: https://sparkgrin-labs.github.io/articles/mcp-core.html

Eliminating state drift and infinite retry loops in local & cloud LLMs (Ollama, vLLM, Claude, OpenAI).

When autonomous agents are given tool-calling capabilities without formal state constraints, probabilistic execution causes sequence jumping (calling tools out of order), infinite retry loops, and lost state on crash.

Agent-FSM forces AI agents into mathematically deterministic, schema-validated state graphs with zero external dependencies:

🛡️ Strict State Transitions: Tool calls outside the active state graph are blocked at the gate.

🔄 SHA-256 Loop Breaker: Detects and halts repetitive tool-calling cycles before tokens are exhausted.

💾 Atomic SQLite Checkpoints: Instant session resumption (--session <id> --resume) after crashes.

📦 100% Python Stdlib: Zero pip dependencies. Instant drop-in into any agent codebase.

💰 Pricing: $29 USD (One-time payment • Lifetime As-Is Commercial License)

🔗 Direct Checkout: https://whop.com/checkout/plan_R1QMTmoTWOkfH

📖 Technical Spec & Benchmarks: https://sparkgrin-labs.github.io/articles/agent-fsm.html