SourceryKit
Python SDK that verifies AI agent tool calls and data integrity at runtime.
SourceryKit
Python SDK that verifies AI agent tool calls and data integrity at runtime.
Data verified Jul 2026
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SourceryKit Description
SourceryKit is a source-available Python SDK (BSL 1.1) that verifies an AI agent's tool calls and outbound requests at runtime, before errors propagate. It intercepts the agent's interactions with external systems (HTTP APIs, databases, and MCP servers), checks each call against a source of truth, and generates cryptographic proofs that downstream systems can verify in real time. A call only goes out if the agent's claims check out, and every outbound call is logged with anything off the trusted-endpoint allow-list blocked. This catches truthful-looking but wrong requests that a network allow-list misses: a payment to the wrong recipient, an API call with tampered parameters, a tool call whose arguments do not match what the user approved. It is built for teams running production agentic workflows where data accuracy and reliability matter, and it integrates with existing observability tools (Arize Phoenix, LangFuse, LangSmith). The SDK is pip-installable and pairs with a hosted backend that runs the proof and source-of-truth check.
SourceryKit FAQ
Common questions about SourceryKit including features, pricing, alternatives, and user reviews.
SourceryKit is Python SDK that verifies AI agent tool calls and data integrity at runtime, developed by Provably. It is a AI Security solution designed to help security teams with Agentic AI Security, LLM Security, MCP Security.
SourceryKit offers the following core capabilities:
1.Runtime verification of agent tool calls before errors propagate
2.Cryptographic proofs checked against a source of truth
3.Hooks HTTP libraries and MCP tool calls, framework-agnostic
SourceryKit integrates natively with Arize Phoenix, LangSmith. Integration support lets security teams connect SourceryKit to existing SIEM, ticketing, identity, and notification systems without custom development.
SourceryKit is deployed as a hybrid solution, suited to startup, mid-market, enterprise organizations looking to operationalize ai security. The commercial offering is positioned for production security operations with vendor support and SLAs.
SourceryKit is built for security teams handling Agentic AI Security, LLM Security, MCP Security. It supports workflows including runtime verification of agent tool calls before errors propagate, cryptographic proofs checked against a source of truth, hooks http libraries and mcp tool calls, framework-agnostic. Teams typically adopt SourceryKit when they need to ai security capabilities integrated into their existing stack. Explore similar tools at https://cybersectools.com/alternatives/sourcerykit
SourceryKit is a commercial AI Security solution. For detailed pricing information, visit https://github.com/ProvablyAI/sourcerykit or contact Provably directly.
Popular alternatives to SourceryKit include:
1.Evoke Security - Agentic AI security platform for inventory, posture mgmt, and threat detection. (Commercial)
2.Onyx Platform - AI control plane for enterprise AI agent security, governance, and observability. (Commercial)
3.JetStream Security-First AI Governance Platform - AI governance control plane for agentic AI visibility, identity, and runtime control. (Commercial)
4.Lunar.dev MCP Gateway (MCPX) - Gateway for securing, governing, and auditing AI agent access to MCP servers. (Commercial)
5.Sonoma Security - MCP governance platform for securing and controlling enterprise AI agents. (Commercial)
Compare all SourceryKit alternatives at https://cybersectools.com/alternatives/sourcerykit
SourceryKit is for security teams and organizations that need Agentic AI Security, LLM Security, MCP Security. It's particularly suitable for enterprises requiring robust, commercial-grade security capabilities. Other AI Security tools can be found at https://cybersectools.com/categories/ai-security
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