"Semantic Search API Solutions" matching MCP servers:

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Enables AI agents to describe combinatorial optimization problems as JSON and obtain validated, ranked, re-verified solutions through MCP tools.

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

Connect AI agents to Jev AI (jev-ai.pro) for classification, scoring, yes/no checks, advisory action assessment, batched typed decisions and saved judges. Returns structured answers and probabilities using your Jev AI API key.

It gives AI agents one tool to access the Omega-API judge, which evaluates conversational turns and returns a decision and gate action (release, clarify, suppress, or none) to guide the agent's response.

A local stdio MCP server that exposes compact semantic observations from UI elements annotated with data-agent-* hints, designed to work alongside the official Playwright MCP for browser automation.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Lets separate coding-agent sessions coordinate through a shared, role-addressed mailbox instead of a human relaying every message, over a single local SQLite file or a hosted server with many isolated channels. Messages can be sent as tracked obligations that stay open until one side resolves and the other confirms, alongside threads, full-text search, work statuses, and an append-only versioned pin system where protected changes require recorded agreement from every declared role.

Enables evolutionary solution generation and optimization using genetic algorithm principles, allowing LLMs to evolve solutions across multiple generations with consistency check evaluations and convergence detection.

Description: Persistent memory for AI agents with rollback, audit trails, semantic search, and knowledge graph. Zero-config local SQLite or cloud API. 23 tools, 6 resources, 3 prompts.

Enables Claude Code to query and control the SuperInstance fleet, including fleet status, conservation law checks, semantic search, and agent registry.

Persistent memory for AI agents with sectioned entries (project/user/context/etc), semantic search, CLI, and per-project scope. Local JSON, zero config, no server required.

Enables any MCP client to browse, triage, search, read, and drive pi coding agent sessions through Pi Web's HTTP API via 25 tools. Supports listing and filtering sessions, reading transcripts, flagging conversations awaiting input, sending messages and waiting for replies, inspecting project diffs, and forking, renaming, or deleting sessions over either stdio or Streamable HTTP.

Semantix-Verify is an MCP server for semantic validation of AI/LLM outputs. It exposes a single tool, verify_text_intent(text, intent_description, threshold), which uses a local quantized NLI cross-encoder (INT8 ONNX) to return a 0.0–1.0 probability that the text satisfies the given intent — and, when it doesn't, a structured correction prompt for agent retry loops. Useful for building com

The best free social media publishing and scheduling API. Publish to 11 platforms from a single API call. Schedule posts, upload media, track analytics, and automate your social media workflow.

Enables AI project feasibility evaluation and solution planning through structured reasoning stages, using Gemini API and web search for up-to-date research.

Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings with keyword fallback. Tools: remember, recall, history, forget, stats.

It gives Claude Code, Cursor, and Codex structured workflows and an MCP server for building data pipelines with dlt - covering REST API ingestion, transformations, data quality, and exploration.

Provides long-term memory capabilities for MCP clients by wrapping the Mem0 API, enabling semantic search, storage, retrieval, and management of conversation memories across users and agents.

A persistent long-term memory server for AI assistants that enables storing and recalling solutions, facts, and decisions with intelligent confidence tracking and relationship mapping. It allows developers to build a cross-platform knowledge base that integrates seamlessly with IDEs and CLI agents.

Provides persistent semantic memory with semantic search, knowledge graphs, and Intelligence Packs for AI agents, enabling memory recall by meaning and session continuity.

Enables developers to delegate asynchronous coding tasks to a cloud-based autonomous agent, creating tasks, reviewing and approving execution plans, sending feedback, monitoring sessions, and retrieving diffs and Pull Requests directly from an MCP-compatible IDE. It also supports configurable mock mode for local testing without consuming API credits.

Enables agents to submit proposed actions against governed domain text and receive proceed, escalate, or block decisions, with persisted review-queue handling over stdio JSON-RPC.

Provides AI coding agents with persistent, traceable memory across projects by storing cue-pointer records that link back to full original contexts, enabling recollection of past decisions, patterns, and solutions.

Provides comprehensive session management for Claude Code with automatic initialization/cleanup, quality checkpoints, and local conversation memory with semantic search for capturing learnings across coding sessions.

Gives AI coding assistants cross-session persistent memory with semantic search and task management, fully local.

Persistent 4-tier AI memory (episodic, semantic, project, procedural) with temporal scoring, contradiction detection, entity tracking, and real-time desktop visualization orb.

This is a MCP server that implements an unreasonable thinking system. It helps generate unconventional solutions: Generating unreasonable thoughts that challenge conventional wisdom. Creating branches of thinking in different directions

Automates GitHub issue-to-PR workflows using specialized AI agents (analyst, architect, developer, tester, reviewer) that analyze requirements, design solutions, implement code, generate tests, and perform code reviews with HIPAA compliance checks.

Enables agentic workflows to execute allow-listed side effects with automatic reverse-order compensation on failure, durable SQLite journaling, and idempotent rollback via MCP tools.

Enables AI agents to interact with the Moltbook social network, including posting, reading feeds, commenting, voting, and semantic search.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

Provides advanced probabilistic decision-making algorithms including MDPs, MCTS, Multi-Armed Bandits, Bayesian Optimization, and Hidden Markov Models to help AI assistants explore alternative solutions and optimize long-term decisions.

A server that enables Claude Desktop users to access the Claude API directly, allowing them to bypass Professional Plan limitations and use advanced features like custom system prompts and conversation management.

A TypeScript-based REST API that integrates project and task management with MCP (Model Context Protocol), allowing users to manage projects and tasks through natural language interactions.

Enables AI agents to perform headless video editing through 35 tools for project creation, clip manipulation, rendering, quality control, and semantic search, all via JSON-RPC 2.0 over stdio.

A Model Context Protocol server that enables AI assistants to interact with the Deriv trading API, providing access to active trading symbols and account balance information.

Enables agents to audit their own reasoning trajectories for loops, deadlocks, and logical contradictions, then perform non-destructive checkpoint rollbacks to a sound prior step. It combines step-level reward evaluation, MCTS search, symbolic proof checking, and consensus voting to return verified solutions over MCP stdio.

Provides persistent memory for AI models by enabling the storage and retrieval of episodic, semantic, and procedural information through the memro protocol. It allows assistants to maintain long-term context via semantic search and chronological memory management.

Connects MCP clients to the 638Labs registry to discover, route, and auction tasks across diverse AI agents. It enables price-based auctions where agents compete to provide the most cost-effective solutions for tasks like coding, translation, and data extraction.