"Finding the best servers for quant trading, options pricing in Python, R, Rust and market data" matching MCP servers:

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

A MCP server to allow the LLM in Cursor to access Rust Analyzer, Crate Docs and Cargo Commands.

Provides retrieval and analysis tools for a quantitative-finance research library, enabling whole-passage answers with verifiable citations, citation checking, entity graph exploration, and corpus inspection.

Enables AI assistants to interact with IG Trading API for forex, indices, and commodities trading. Provides 21 tools for account management, position trading, order placement, market data analysis, and watchlist management.

Skill librarian for coding agents: describe a task and get the few matching skills from a large local skill collection, then report whether they worked. Runs locally with Ollama and SQLite.

Enables AI clients to search curated, cited knowledge bases built from founders', CEOs', and investors' public talks, essays, and posts, returning passages with source links and dates. It also exposes available source collections via MCP tools so users can ask how those individuals might approach business, product, or growth questions.

Enables an agent to submit a task brief and receive a short, validated list of skills from its full catalogue that are worth reading before starting.

Enables AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

Enables AI agents to conduct local, auditable opportunity discovery by collecting public discussions, tracing claims to exact quotes and source provenance, testing claims with counterevidence, and exporting deterministic evidence packs.

A Python MCP server providing AI agents with tools for local knowledge base search, business context retrieval, and text summarization prompt generation.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

A Model Context Protocol server that exposes over 200+ APIs from API.market as MCP resources, allowing large language models to discover and interact with various APIs through natural language commands.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

Provides a retrieval/MCP knowledge server for the Unreal Engine Python API, enabling AI agents to retrieve real signatures and documentation before writing code.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables AI agents to automate and navigate Naver SmartStore administration by providing screen and selector maps, Talk CS handling, three-step safety approvals, official help-document RAG, and search ad keyword tools.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

A proof of concept MCP server for Apache OFBiz

Enables loading CSV text, filtering and aggregating datasets over Streamable HTTP, and optionally using Amazon Bedrock to turn query results into concise answers suitable for speech.

Enables agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.

Provides semantic search and complete document retrieval by ID through OpenAI's Vector Store API, letting deep research agents access company-specific knowledge and tools.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.