"oracle" matching MCP servers:

Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.

Enables Codex to delegate tasks to ChatGPT through a browser-backed Oracle connection, with project memory and a verified-result cache. It supports preview, delegation, result polling, and explicit acceptance without an API fallback.

Provides real-time LLM pricing and availability data as an MCP server, enabling AI agents to make optimal model routing decisions at inference time with cited pricing sources.

MCP server exposing AIMarket's verifiable oracle capabilities (Platon VRF, Chronos VDF, LUMEN reputation) as agent-callable tools with pay-per-call.

On-chain TCG price oracle for the LitecoinVM ecosystem. 6 tools: search 433K+ trading cards, 60-day price history, Merkle proof verification on LiteForge (Chain 4441), Monte Carlo simulation, and AI card grading via Qwen 2.5 VL.

DCL Trust Oracle is a deterministic AI audit layer, natively integrated with MCP, that evaluates LLM and agent outputs against configurable policies before and after action. Every verdict is written to a tamper-evident, hash-chained audit log storing only cryptographic metadata — never raw content — enabling privacy-first forensic review.

TCG oracle as an MCP server: 22 focused tools. Search 455K+ trading cards, live market snapshots, AI grading and grade-or-not decisions, conformal-calibrated price forecasts with a public accuracy scorecard, card-collateral loan terms, fantasy and sports souls leagues. Every root proven on-chain. Same tools as the hosted endpoint at mcp.the-undesirables.com, over stdio; no keys.

Enables AI agents to query cryptographically verified facts with zero-knowledge proofs, selective disclosure, and tamper-evident provenance.

Darknet threat intelligence MCP server with 10 tools powered by 12,000+ vectorized data points from IronClaw pipeline.

Enables AI-powered database operations on Oracle Autonomous Database via natural language, including SQL translation, schema exploration, and API orchestration.

Access control for text-to-SQL agents. Before the model sees the schema, schemagate keeps only the tables and columns the caller may read, picks the few a question needs, and refuses hidden ones at query time. Postgres, Oracle, MySQL, SQL Server, SQLite. Quantum-safe signed audit log. Try it in your browser: https://ashishsinha1602.github.io/schemagate/

LLM pricing oracle — model lookup, cost estimation, and comparison via LiteLLM. An MCP server that gives AI assistants accurate, up-to-date model pricing from the LiteLLM community registry. Look up pricing and capabilities for any LLM with fuzzy matching, estimate costs for token volumes, and compare models by provider, context window, or mode.

Enables OCI Enterprise AI models to invoke published Oracle Fusion AI Agent Studio workflows as MCP tools, handling Fusion tokens, asynchronous workflow invocation, bounded polling, and returning answers with evidence of the MCP call. Also provides a browser demo page with a direct Fusion test route alongside the full EAI-to-Fusion MCP path.

Enables users to ask plain-English questions against MySQL, PostgreSQL, SQLite, SQL Server, Oracle, and MariaDB databases by auto-detecting schemas and converting requests into safe, read-only SQL queries.

Exposes selected Swagger Petstore GET operations as callable tools for querying pets by status, tags, or ID. Supports deployment with OCI Generative AI and live testing through the Responses API.

Enables LLM agents to connect to and retrieve data from multiple database types through a unified API, including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift. It supports schema normalization and query transformation to make database access more compatible with natural-language workflows.

Enables LLM agents to connect to and retrieve data from a wide range of databases — including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift — through a single unified API. It also normalizes schemas for LLM compatibility, optimizes generated queries, and transforms them back into their original form for execution.

Enables AI assistants to query relational databases like MySQL, PostgreSQL, and Oracle using natural-language questions, dynamically discovering schemas and generating validated read-only SQL through configurable AI providers such as Groq, Claude, and Gemini.