"Semantic layer for SQL query execution with dimensions and measures" matching MCP servers:

Enables agents to interact with a governed semantic layer for querying and authoring metrics, providing tools for discovery, planning, validation, and execution of analytics queries.

MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.

Enables AI agents to store, search, and recall semantic memories with three memory types (semantic, episodic, procedural) and auto-consolidation, compounding intelligence over time.

Embedding space analysis toolkit that measures semantic drift, traces trajectory dynamics, and projects passages onto caller-defined semantic axes, exposed as MCP tools for agentic integration.

Enables Codex to run shadow-mode evidence selection by reading source files, scoring passage relevance with Jev or local Eve models, and returning original text with provisional exclusion decisions.

Enables natural-language querying of a SQLite database through a locally served, fine-tuned text-to-SQL model exposed as an MCP tool, offering fast and cost-free SQL generation and execution.

Enables agents to verify claims with evidence-based truth scores and confidence levels by running a deterministic pipeline of evidence lanes and adversarial checks.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Enables LLM agents to make fast semantic decisions by choosing one of 2–16 options with probabilities, via tools for single and batch classification.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

Enables querying a PostgreSQL database using natural language by retrieving context from Azure AI Search and generating SQL with Azure OpenAI, with validation and optional execution.

Enables local coding agents to delegate reasoning, planning, review, derivation, and diagnosis tasks to ChatGPT Web through Chrome DevTools Protocol, with security guards and evidence-based verification.

Model Context Protocol (MCP) server that gives AI assistants a safe, correct data-analyst capability over business metrics - without raw SQL improvisation.

An MCP server that transforms natural language questions into SQL, executes queries on PostgreSQL, and returns human-friendly responses, with Redis memory for context.

A local DLP middleware that redacts sensitive information from prompts using local models before they reach external LLMs. It provides tools to sanitize queries, restore placeholders in responses, and manage a ledger of redactions to maintain data privacy.

Enables agents to deduplicate semantic prompt caches by measuring Jaccard token overlap, preventing redundant LLM calls and reducing cost. It provides deterministic lookup-or-insert cache behavior through an MCP-compatible interface.

Enables estimating LLM hallucination and confabulation by clustering sampled responses into semantic equivalence classes and computing semantic entropy. It provides a plug-and-play validation filter for agent pipelines using the MCP protocol.

Enables detecting LLM hallucinations and confabulations by clustering sampled responses into semantic equivalence classes and computing semantic entropy.

Provides LLMs with persistent memory and reusable skills via MCP, enabling semantic storage and retrieval of user preferences, project context, and step-by-step procedures across conversations.