"Resources or information on analysis techniques or methods" matching MCP servers:

A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.

A lightweight MCP server for intelligent, non-invasive analysis of Obsidian vaults.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

MCP server for persistent project knowledge management, enabling AI assistants to store, search, and reuse project analysis insights with freshness checking and impact analysis.

MCP server that parses aviation accident reports (PDF/DOCX/TXT) and injects their content into extraction prompt templates for knowledge graph construction.

Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Enables qualitative analysis through a strict TypeDB ontology that verifies evidence quotes and refuses method-breaking changes, while agents use MCP tools to add concepts, themes, dimensions, memos, and checkpoints. Supports append-only event logs for replay, forking, and comparison across staged analysis runs.

A Model Context Protocol (MCP) server for interacting with MongoDB stock data to provide portfolio recommendations and market insights, exclusively for the Indian stock market (NSE/BSE).

Provides tools for Bazi (Chinese astrology) chart calculation and analysis, enabling LLMs to generate accurate birth charts, determine patterns, and answer follow-up questions based on actual calculations rather than model knowledge.

Agent memory on a local SQLite file or on PostgreSQL with pgvector, with provenance, trust verdicts and explicit abstention when memory cannot support an answer.

Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.

Lets AI clients store, retrieve, update, and forget long-term facts in a local SQLite database with deterministic lexical search, sharing the same memory across multiple clients without relying on model APIs or embedding services.

Provides tools for managing student knowledge graphs, enabling structured representation of courses, assignments, exams, concepts, and study resources.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Provides AI coding tools with one local SQLite memory and rules store they can read over MCP, REST or the CLI, so facts, sessions and goals persist across sessions and shared rules are written into each tool's own instruction file. Runs entirely on your machine with no account, telemetry or network calls by default.

Enables Claude chats to communicate across machines or sessions via shared encrypted rooms, with tools to create, join, send, read, wait, search, and delete room messages.

Scans local folders for PDF papers, extracts title/abstract text, and moves files to categorized folders based on classification decisions made by Claude or another MCP server.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

A knowledge-based MCP server for Ozon sellers, enabling AI agents to search a 42-lesson Chinese operations playbook and discover/call over 460 Seller and Performance API methods for real business actions.

An MCP server that stores notes as Markdown files on your machine, enabling you to save, search, and manage notes through natural language with Claude Code or Claude Desktop.

Provides MCP tools to read, write, append, and edit prose sections of nodes, backed by an in-memory or substrate-direct (Urania) backend.

Hermetic memory for AI agents — one Rust binary, one SQLite file, zero network. Recall returns evidence with provenance or abstains: no code path for making things up.

Search past OpenCode conversation history before starting new work on a module or file, via a local read-only FTS5 index built from OpenCode's own SQLite database. No network calls, fully local. 7 tools for keyword search, file lookup, and session browsing.

Local-first, source-traceable memory for AI agents — no LLM at ingest, $0 per message, zero data egress. Gives Claude Code, Cursor, and any MCP client one shared persistent memory with semantic recall, belief revision, selective forgetting, and a provenance guard that blocks acting on stale or unconfirmed memories.

Enables LLMs to maintain persistent memory by reading and writing Markdown notes and sibling image assets in a user-selected local or sync folder, with no cloud service, account, or server to run.

Agent memory for facts that change. When a user corrects something, Recall replaces the old fact, tells the agent what it replaced, and keeps the old value in a history. Ask what was believed on any date, see every change to a fact, or diff two dates. Runs locally on polign_db, Postgres with pgvector, MongoDB, or Qdrant. Apache 2.0.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

MCP server for World Anvil that enables browsing, searching, and managing world content, plus exporting complete copies for migrations or backups.

Self-hosted memory for your AI, kept in your own git repo: Markdown and HTML it reads and writes, beside PDFs, office files, images and JSON it reads as they are. 34 tools to search, read, write and file notes. Every change is attributed to a person or an AI, an agent's work undoes in one step, any note reads as it was on any date. Flags contradictions. Runs over stdio or as a server with OAuth.

Shared memory for AI coding agents (Claude Code, Codex, Cursor and others) in one local SQLite file, over MCP or REST. Every note records which agent wrote it and keeps its history; writes that match known prompt-injection patterns are held for your review; you can roll back everything one writer did. Runs on your machine, no cloud or API keys, MIT licensed.

Read-only recall over your past Claude Code, Codex, pi and Hermes sessions: semantic search for past decisions, rationale and findings, plus tools to list sessions, get the gist of one, find exact strings in it and read its turns. Works on your local memory or on any memory published as a Hugging Face dataset.

Shared memory MCP server for AI coding agents, enabling context sharing across sessions with local SQLite or cloud-based semantic search, compatible with Claude Code and Cursor.

Exposes the MITRE ATT\&CK framework to LLMs and AI assistants via the Model Context Protocol, enabling querying of techniques, tactics, groups, software, and mitigations.

A local MCP server that exposes Mem0 as persistent memory tools to any MCP client, storing data locally with no cloud API or API key required.

MCP server that exposes a resume as callable tools and resources, enabling AI agents to query experience, skills, projects, and contact information via natural language.

Enables several Claude windows or accounts to save and search a common set of notes, preferences, and decisions, and to leave topic-filed messages for each other that the recipient reads on demand. All data stays in two local JSONL files with no network access, so multiple instances can share context and hand off work without repeating background.

Enables saving, searching, retrieving, linking and importing AI work as plain markdown files with automatic provenance in a local folder the user owns. Runs entirely on the user's machine with no account, key or network calls, and never deletes anything.

Enables Claude AI to seamlessly interact with Scrivener projects for document management, AI-powered content analysis, and advanced writing assistance.

Serves organizational context to MCP-capable AI agents from a local folder or GitHub repository, and lets agents propose changes that require human approval.