Elasticsearch MCP Server MCP Server Pricing 2026
Updated June 2026Complete pricing guide for the Elasticsearch MCP ServerMCP server — costs, free options, and what you'll pay.
💰 How Much Does Elasticsearch MCP Server MCP Server Cost?
The MCP server is free and open-source. Elasticsearch: Open-source and free to self-host. Elastic Cloud: Free trial, then from $95/mo. Enterprise: Custom.
See official Elasticsearch MCP Server pricing →Is Elasticsearch MCP Server MCP Server Free?
The Elasticsearch MCP Server MCP server itself is free to install and use. The underlying Elasticsearch MCP Server service offers a free tier that lets you get started without paying. Paid plans are available for additional features and higher usage limits.
Elasticsearch MCP Server Cost Breakdown: Server vs Service
MCP Server (Always Free)
The Elasticsearch MCP Server MCP server is the connector that lets your AI assistant (Claude, Cursor, VS Code, etc.) interact with Elasticsearch MCP Server. This component is always free to install and use — it's just a bridge between your AI tool and the service.
Elasticsearch MCP Server Service (Freemium)
The MCP server is free and open-source. Elasticsearch: Open-source and free to self-host. Elastic Cloud: Free trial, then from $95/mo. Enterprise: Custom.
View official pricing →How to Install Elasticsearch MCP Server MCP Server
docker run -i --rm -e ES_URL -e ES_API_KEY docker.elastic.co/mcp/elasticsearch stdioCompatible with: Claude Desktop, Cursor, VS Code, Windsurf, Cline
Frequently Asked Questions
Is Elasticsearch MCP Server MCP Server free to use?
The Elasticsearch MCP Server MCP server itself is free to install. The underlying Elasticsearch MCP Server service offers a free tier with limited features, plus paid plans for additional capabilities.
How much does Elasticsearch MCP Server MCP Server cost in 2026?
The MCP server is free and open-source. Elasticsearch: Open-source and free to self-host. Elastic Cloud: Free trial, then from $95/mo. Enterprise: Custom. The MCP server component is always free to install and configure with your AI assistant.
What are the best alternatives to Elasticsearch MCP Server MCP Server?
There are several alternative MCP servers in the Search category. Visit the Elasticsearch MCP Server alternatives page on MyMCPTools to compare features, pricing, and compatibility with AI assistants like Claude, Cursor, and VS Code.
What's included in the Elasticsearch MCP Server free tier?
The Elasticsearch MCP Server free tier typically includes core functionality with usage limits. Check the official Elasticsearch MCP Server website for the most up-to-date free tier details and limitations.
Does Elasticsearch MCP Server work with Claude Desktop, Cursor, and VS Code?
Yes, the Elasticsearch MCP Server MCP server is compatible with popular AI assistants and code editors that support the Model Context Protocol (MCP), including Claude Desktop, Cursor, VS Code, Windsurf, and Cline.
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Compare similar MCP servers with different pricing and features.
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Quick Info
- Pricing Model
- Freemium
- Install Type
- docker
- Author
- Elastic
- Categories
- 🔍 Search🗄️ Database
- Source Code
- View on GitHub →
- Official Pricing
- View Pricing →
Related Servers
The Apify MCP server gives AI agents access to 6,000+ ready-made cloud scrapers, crawlers, and automation tools on the Apify Store — no infrastructure required. Connect to Apify Actors that extract data from social media platforms (Instagram, TikTok, LinkedIn), search engines (Google, Bing), e-commerce sites (Amazon, eBay), maps (Google Maps), and virtually any website. Each Actor runs in the cloud with managed proxies, browser fingerprinting, and anti-bot bypass built in. Use the Apify MCP server to query Actors by task, stream results directly into your AI context, run custom scraping Actors from your Apify account, and chain multiple data extraction steps in a single workflow. Supports tool filtering to expose only the Actors you need, and integrates with Apify's RAG web browser Actor for retrieval-augmented generation use cases.
The Firecrawl MCP server gives your AI assistant the ability to crawl, scrape, and extract structured data from any website — turning raw HTML into clean, LLM-ready Markdown or JSON in seconds. Built by the Firecrawl team, it exposes tools for single-page scraping, deep site crawls (following internal links), and batch URL extraction, all with JavaScript rendering handled automatically so dynamic content is never missed. Developers use it to automate competitive research, build live knowledge bases, extract pricing tables, monitor documentation changes, or feed structured web data into RAG pipelines — all through natural-language prompts without writing a single scraper script. The Firecrawl MCP server handles rate limiting, retries, and proxy rotation behind the scenes. Authentication requires a Firecrawl API key (free tier available). Install with: npx firecrawl-mcp. Works with Claude Desktop, Cursor, VS Code, and any MCP-compatible client. With Firecrawl, any public webpage becomes a structured data source your AI can reason over, compare, and act on — making it the go-to MCP server for web data extraction workflows.
Exa's official MCP server connects AI assistants to a search engine purpose-built for AI, using neural embeddings to match on meaning rather than keywords so agents get clean, ready-to-use content instead of a page of blue links to re-parse. The default tool set covers web_search_exa for quick topical lookups and web_search_advanced_exa for full control over domains, date ranges, and content filters, plus specialized tools for code_search (searching real-world code and GitHub), company_research (building company profiles, competitor lists, and financials), crawling/web_fetch (pulling clean content from a specific URL), people_search and linkedin_search (public professional-profile lookups), and deep_researcher_start/check for long-running multi-step research tasks backed by Exa's Research API. The server is hosted at https://mcp.exa.ai/mcp — no local process to run — and connects via one-line setup in Cursor, VS Code, Claude Code, Claude Desktop (available as a native Connector), Codex, OpenCode, Windsurf, and Antigravity, authenticated with an EXA_API_KEY from the Exa dashboard. Tool exposure is tunable per client via a ?tools= query parameter on the endpoint URL, letting teams ship narrow, purpose-built configurations (e.g. company-research-only or LinkedIn-only agents) instead of exposing the full surface, and Exa ships ready-made Claude Skills/agent definitions for common patterns like company research and people search with built-in query-variation and token-isolation guidance.
The Brave Search MCP Server is the official server from Brave that gives AI assistants privacy-first web search through the independent Brave Search API — no tracking, no profiling, and results drawn from Brave's own web index rather than Google or Bing. It exposes five distinct tools that map directly to the Brave Search API endpoints: brave_web_search for general queries with pagination, freshness filters, and safe-search controls; brave_local_search for businesses, restaurants, and points of interest with automatic location filtering; brave_news_search for recent articles and current events; brave_image_search for image discovery; and brave_video_search for finding videos across the web. Authentication uses a single BRAVE_API_KEY (free tier available at brave.com/search/api) or a mounted BRAVE_API_KEY_FILE for Docker-secret setups. Install in Claude Desktop, Cursor, Windsurf, or VS Code with one npx command and choose stdio or streamable-HTTP transport. Because Brave operates its own crawler and index, the Brave Search MCP server is a strong choice for developers who want an alternative to Google-dependent search tools, need reproducible non-personalized results, or care about data privacy in agent workflows — Claude can pull fresh web context, verify facts, and research topics without leaking queries to ad-tech pipelines.
The official MongoDB MCP server, `mongodb-js/mongodb-mcp-server`, maintained by MongoDB. Searchers find it as the MongoDB MCP server or the Mongo MCP server; both names refer to this one project, and there is no separate short-form server. It is really two tool surfaces in one process. The database tools connect to any MongoDB deployment over a connection string in `MDB_MCP_CONNECTION_STRING` — `find`, `aggregate`, `explain`, `collection-schema`, `collection-indexes`, `create-index`, `count`, `export`, `mongodb-logs` and the write tools — or, if no connection string is set, the model calls the `connect` tool at runtime and passes the returned `connectionId` to later calls. The Atlas tools are a separate control plane: listing and creating clusters, database users, IP access-list entries, stream processing resources and the performance advisor. They authenticate with Atlas Service Account credentials (`MDB_MCP_API_CLIENT_ID` / `MDB_MCP_API_CLIENT_SECRET`), not with a connection string, and they simply do not register when those are unset — the usual cause of a 'the Atlas tools are missing' report. Two defaults are worth knowing before you point it at production. `readOnly` is false, so every write tool including `drop-database` is registered unless you pass `--readOnly`, which is why MongoDB's own README uses that flag in every example. And confirmation-required tools rely on MCP elicitation, so on a client that does not support elicitation they execute without prompting — `--readOnly` or `--disabledTools` is the actual boundary. Other guardrails: `indexCheck` rejects queries that would do a collection scan, server-side JavaScript (`$where`, `$function`, `$accumulator`) is disabled by default, results are capped at 100 documents and 16 MB per call, and `--dryRun` prints the resolved config and enabled tool list without starting the server. Requires Node 22.13.0 or later (Node 20 is deprecated); also published as the `mongodb/mongodb-mcp-server` Docker image. Runs over stdio by default, with an optional HTTP transport and a separate monitoring listener for `/health` and Prometheus `/metrics`.
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