Veritas Gateway: A Framework for Zero-Knowledge Proofs on Database Queries with a Model Context Protocol Interface

Veritas Gateway is a zero-knowledge verification layer that acts as an intermediary between AI agents and diverse data stores through the Model Context Protocol (MCP). Database snapshots are committed to with Poseidon based Merkle commitments and query answers are returned with succinct SNARK proofs that can be locally verified without satisfying predicates on raw values or trusted hardware. The prototype implements this stack across relational, NoSQL, time-series and vector databases through generic adapters and is empirically evaluated along four dimensions: scalability across MySQL as snapshot size and Merkle height varies, a hash-primitive ablation study with Poseidon, MiMC-7 and SHA-256, a proof-system ablation across Groth16, PLONK and STARKs on a common circuit, and horizontal portability across SQLite, PostgreSQL, MongoDB, InfluxDB and Qdrant under a fixed workload. Measurements include build time, proving time, query time, query assembly time, query verification, memory footprint, and derived throughputs. It is found that build time increases predictably with snapshot size and height, proving cost is driven by path depth and is consistent across iterations, query assembly time is consistently sub-second, and verification completes in ≈ 8 − 12 ms across all settings. Poseidon incurs the lowest in-circuit latency and variance, with SHA-256 only competitive for out-of-circuit pre-hashing. Groth16 results in the shortest verified-latency path, PLONK results in a reduction of proving time, and STARKs result in transparent setup at a higher memory cost. Cross-backend variation is dominated by build overhead and the data-path overheads for each backend’s cryptographic verification, for which cost is never a bottleneck. These results suggest that Veritas Gateway provides backend-agnostic, verifiable querying with predictable latency, improving trust in the MCP-driven agent workflow while maintaining the benefits of tool-based integration and facilitating deployment in privacy-sensitive environments.