"Gcore" matching MCP servers:

Enables interaction with the Sond Core API through the Model Context Protocol. Auto-generated from the OpenAPI specification at https://core-api-lb.sond.com/api-json to provide programmatic access to Sond's services.

Local-first operator MCP server: recall across your own sessions, chats and files, an encrypted vault, SSH to your own hosts, and gated shell, browser and device tools. 130 tools over stdio or HTTP; everything runs on your machine — no hosted service, no account, no API key.

A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.

Run local AI across all your computers. Toskar's MCP server lets Claude, Cursor, and other clients ask your own local models and search your connected knowledge, with nothing leaving your machines.

Shared, versioned memory for your agents across Claude Code, Cursor, Kiro and Grok. One MCP server, sourced answers, full history.

Local MCP server for specialist personas, reusable Markdown workflows, task-scoped subagent contracts and per-repository memory. Runs on your own computer with Python 3.11+ and a locally installed embedding model; its Claude Code plugin launches that separate installation.

Read, cite, compose and remember over a Markdown knowledge Bundle, as MCP tools over stdio.

Provides zero-knowledge, local-first persistent memory for AI assistants with on-device embeddings, cross-platform capture, and zero-RTT semantic recall.

Enables coding agents to search a locally indexed codebase with hybrid dense, lexical, and symbol-graph retrieval, returning ranked passages with exact file:line-line citations plus graph context and index status. It keeps its index in sync via a file watcher and runs as a local sidecar with no hosted service to deploy.

Enables MCP-capable clients to search a folder of Markdown notes with hybrid full-text and embedding retrieval, plus read, write, append, and reindex operations that keep a single shared SQLite index in sync with the files.

Enables AI agents to perform fused hybrid search and reorganize documents, folders, and metadata in the SAGA document archive via MCP tools.

Personal digital memory: a desktop app that indexes your mail, chats, and documents into a local SQLite corpus on your machine — parsing and OCR run on-device via llama.cpp — and serves them to any MCP client. Local server on 127.0.0.1, plus an optional per-user remote endpoint (you.localkiagent.com) whose TLS terminates on your own device.

Enables AI clients to interact with Letta.ai's stateful agents via cloud deployment on Railway. Provides 20+ tools for agent management, conversations, memory operations, and tool configuration through a streamable HTTP transport optimized for production use.

A headless local knowledge library and RAG substrate that enables LLM clients to search, retrieve chunks, and list documentation packs through read-only MCP tools.

Enables AI agents to get read-only trust verdicts on knowledge records by evaluating evidence maturity, provenance, intended use, risk level, and scope before deciding whether knowledge may be used.

Enables AI agents to search, filter, and explore a local offline catalog of tools from awesome lists, including finding underrated tools, explaining ranking provenance, listing curator lists, and inspecting catalog facets. All access is read-only over local SQLite with no network calls or API keys.

Enables autonomous multi-agent workflows to capture, preserve, and retrieve immutable transcripts and atomic memory cards through a local MCP server, providing tools for forensic search, topic mapping, and structured fact access without losing context fidelity.

Enables AI applications to store facts and relationships as structured, tenant- and project-scoped memory in PostgreSQL, then retrieve relevant context across sessions and update, supersede, or delete individual facts. It also exposes capability discovery and batch fact storage tools so assistants and agents can maintain memory they can inspect and evolve.

Enables MCP-compatible agents to read explicitly specified persona files, long-term memories, daily summaries, and valid continuation cards through read-only context tools. It supports keyword recall and limited source retrieval with source numbering and eligibility re-checks.

Provides deterministic, read-only access to engineering decisions, requirements, and designs stored as Markdown in a repository, enabling agents to retrieve and follow decided context without embeddings or external services.