Best Excel MCP Server MCP Server Alternatives 2026
Updated June 202610 alternatives to Excel MCP Server for your AI workflow. Compare features, pricing, and compatibility.
Excel MCP Server
Open SourceExcel MCP Server (by haris-musa, nearly 4,000 GitHub stars) lets AI agents create, read, and edit Excel workbooks without Microsoft Excel installed anywhere in the pipeline. It's a Python-based server exposing tools across the full spreadsheet lifecycle: creating and modifying workbooks and worksheets, writing formulas, building and styling Excel Tables, generating charts (line, bar, pie, scatter, and more), constructing dynamic pivot tables for analysis, and applying rich formatting — fonts, colors, borders, alignment, and conditional formatting rules. Built-in data validation keeps ranges, formulas, and cell contents consistent as an agent edits a file. The server supports three transports: stdio for local single-user setups (the default for Claude Desktop and Claude Code), plus SSE and streamable HTTP for remote deployments — when running remotely, set the EXCEL_FILES_PATH environment variable so the server knows where to read and write files, and FASTMCP_PORT to control the listening port. This makes it equally useful for a solo analyst automating a weekly report locally and for a team running a shared Excel-manipulation service that multiple agents call into. Because it operates on the raw XLSX format directly, there's no licensing dependency on Excel itself, and workflows like "pull this CSV into a formatted table with a pivot summary and a bar chart" become a single natural-language request instead of a manual multi-step process.
This MCP server is free and open-source. Check the GitHub repository for details.
Top Excel MCP Server Alternatives
sandboxed read, write, edit, move and search access to an explicit whitelist of local directories, and it is the reference implementation most other filesystem MCP servers are modelled on. Shipped by Anthropic in the official modelcontextprotocol/servers monorepo (89,000+ stars, actively maintained), it is a Node.js server published to npm as @modelcontextprotocol/server-filesystem. The part worth understanding before you install is the access-control model, because there are now two ways to grant directories and they do not compose. Method one is command-line arguments: `npx -y @modelcontextprotocol/server-filesystem /path/one /path/two`. Method two, and the one the maintainers recommend, is MCP Roots — a client that supports the roots protocol sends its roots at initialization, and those roots COMPLETELY REPLACE any directories passed on the command line, then get replaced again on every `notifications/roots/list_changed`. That means allowed directories can change at runtime without restarting the server, but it also means a roots-capable client silently overrides your CLI arguments. If the server starts with no arguments and the client either does not support roots or sends an empty list, initialization throws an error. The tool surface is broad: `read_text_file` (with mutually exclusive `head`/`tail` line windows), `read_media_file` returning base64 image/audio content blocks, `read_multiple_files` which keeps going when individual reads fail, `write_file`, `edit_file`, `create_directory`, `list_directory`, `list_directory_with_sizes`, `move_file`, `search_files`, `directory_tree`, `get_file_info` and `list_allowed_directories`. `edit_file` is the one to learn — it does line-based and multi-line pattern matching with indentation detection and preservation, returns a git-style diff with context, and supports `dryRun: true` so you can preview a change before applying it; the maintainers recommend always running a dry run first. Every operation is refused outside the allowed set, and `list_allowed_directories` is the fastest way to confirm what the server actually believes it can touch.
Free and open-source by Anthropic. Operates on your local filesystem with no external dependencies or costs.
ClickHouse MCP Server is ClickHouse's official MCP server (ClickHouse/mcp-clickhouse) that connects Claude, Cursor, and other MCP clients to a ClickHouse cluster for fast analytical querying over natural language. Its primary tool, run_query, executes arbitrary SQL against your cluster in read-only mode by default (CLICKHOUSE_ALLOW_WRITE_ACCESS=false) so an AI assistant can explore tables, aggregate billions of rows, and answer analytics questions without risk of mutating data — writes can be enabled explicitly when needed. Companion tools list databases and tables and return schema metadata (including the full create_table_query, with an option to omit per-column detail for lighter responses). A second tool set embeds chDB, ClickHouse's in-process engine, via run_chdb_select_query, letting the assistant query files, URLs, and external databases directly without an ETL step (enabled with the optional mcp-clickhouse[chdb] extra). Destructive statements are gated a second time: even with writes enabled, DROP and TRUNCATE require CLICKHOUSE_ALLOW_DROP=true as well. The server supports both stdio and HTTP/SSE transports; on HTTP/SSE authentication is required rather than optional — startup fails unless a static bearer token (CLICKHOUSE_MCP_AUTH_TOKEN), a FastMCP OAuth/OIDC provider (Azure Entra, Google, GitHub, WorkOS via FASTMCP_SERVER_AUTH), or an explicit local-development opt-out (CLICKHOUSE_MCP_AUTH_DISABLED) is configured. Connection is configured through CLICKHOUSE_HOST, CLICKHOUSE_PORT, CLICKHOUSE_USER, and CLICKHOUSE_PASSWORD, with ClickHouse Cloud, self-hosted, and the public SQL playground all supported.
The MCP server is free and open-source. ClickHouse Cloud: Free trial available. Pay-as-you-go pricing. Self-hosted ClickHouse is free and open-source.
The Sentry MCP Server is Sentry's official Model Context Protocol integration, purpose-built for human-in-the-loop coding agents like Claude Code, Cursor, and Windsurf. Rather than exposing every Sentry API endpoint, it focuses tightly on developer debugging workflows: searching and triaging issues, pulling stack traces and event details, inspecting performance traces, and querying project/team/org metadata in natural language. The primary deployment is a hosted remote MCP server at mcp.sentry.dev, built on Cloudflare's remote-MCP infrastructure, so most users connect with zero local setup — just add the remote URL to their client. For self-hosted Sentry instances or local development, a stdio transport is also available via npx @sentry/mcp-server, authenticated with a Sentry User Auth Token scoped to org:read, project:read, project:write, team:read, team:write, and event:write. AI-powered search tools (search_events, search_issues) translate natural-language queries into Sentry's query syntax, but require a configured LLM provider (OpenAI, Azure OpenAI, Anthropic, or OpenRouter) — all other tools work without one. Claude Code users can also install it as a plugin (claude plugin install sentry-mcp@sentry-mcp) for automatic subagent delegation whenever a conversation touches Sentry errors, issues, or traces. This turns "why did this deploy break in production" into a direct conversational debugging session instead of tab-switching into the Sentry dashboard.
The MCP server is free and open-source. Sentry: Developer tier (free, 5K errors/mo). Team: $26/mo. Business: $80/mo. Enterprise: Custom.
The Datadog MCP Server is Datadog's official, vendor-hosted Model Context Protocol endpoint — not a package. Each Datadog site has its own URL of the form https://mcp.<your-site>/api/unstable/mcp-server/mcp (US1: mcp.datadoghq.com, EU1: mcp.datadoghq.eu), and OAuth 2.0 is the recommended way in; a Personal or Service Access Token as an Authorization bearer header is the documented fallback for CI, with DD_API_KEY plus DD_APPLICATION_KEY headers as a third option. Datadog ships first-party client integrations rather than expecting hand-written config: a Claude Code plugin (/plugin install datadog@claude-plugins-official, then /ddsetup and /ddtoolsets), a Claude connector from the Connectors Directory, plugins for Cursor, VS Code/Copilot, JetBrains and OpenCode, and a ChatGPT app in Preview for US1. Tools are grouped into toolsets selected with a ?toolsets= query parameter, and only `core` — logs, metrics, traces, dashboards, monitors, incidents, hosts, services, events, notebooks — loads by default; two dozen more cover alerting, DBM, DDSQL, RUM, profiling, security, Kubernetes, error tracking, feature flags, cost management and data observability, with apm, cases, code-exec and remote-actions in Preview and excluded from toolsets=all. Access requires the mcp_read or mcp_write role permission in addition to the normal resource permission, which is why a working connection can still return no data. Limits at time of writing are 50 requests per 10 seconds of tool-call burst and 50,000 tool calls per month, and the server is not GovCloud compatible.
The MCP server is free and open-source. Datadog: Free tier (5 hosts). Pro: $15/host/mo. Enterprise: $23/host/mo. Additional products priced separately.
The official Grafana MCP server connects Claude and other AI assistants directly to your Grafana instance and its surrounding observability ecosystem, turning natural-language questions into dashboard lookups, incident investigations, and datasource queries. Dashboard tools cover search, retrieval, JSONPath-scoped property extraction, patch-based editing, and per-panel query/datasource introspection, with context-window-aware helpers like get_dashboard_summary so an agent never has to pull a full multi-megabyte dashboard JSON just to answer a simple question. Query tools speak PromQL against Prometheus (including histogram-percentile helpers), LogQL against Loki, and native query languages for InfluxDB, ClickHouse, CloudWatch, Graphite, Athena, Snowflake, Elasticsearch/OpenSearch, and Quickwit datasources — most gated behind opt-in --enabled-tools flags to keep the default tool surface lean. It also wraps Grafana Incident for creating and updating incidents, Sift for automated error-pattern and slow-request investigations, full alerting CRUD (rules, contact points, notification policies) across Grafana-managed and external Alertmanager sources, Grafana OnCall schedule/shift/alert-group management, RBAC-gated admin tools for teams/users/roles, deeplink generation so the LLM never has to guess a dashboard URL, annotations, snapshots, PNG rendering via the Grafana Image Renderer, and provisioning-repo validation for git-sync workflows. Authentication is a Grafana service account token (Editor role, or granular RBAC scopes) passed as GRAFANA_SERVICE_ACCOUNT_TOKEN alongside GRAFANA_URL, and every tool category can be individually disabled to control context-window usage. On install, the recommended route is uvx: `uvx mcp-grafana` pulls the PyPI package mcp-grafana, which is published by Grafana Labs from this same repository — so despite the server being written in Go, the copy-paste command most Claude Desktop and Cursor configs use is a Python-tooling one, not a binary download. The alternatives are `go install github.com/grafana/mcp-grafana/cmd/mcp-grafana@latest` for a real binary, or the grafana/mcp-grafana container — `-t stdio` for local clients, or the default HTTP mode on :8000 (add `-t streamable-http`) with MCP_GRAFANA_SERVER_TOKEN set to authenticate callers when you expose it.
The MCP server is free and open-source. Grafana Cloud: Free tier (10K metrics, 50GB logs). Pro: $29/mo. Advanced: $299/mo. Self-hosted is free.
Anthropic's reference Model Context Protocol server for Google Drive — and a retired one, which is the first thing to know about it. The repository moved to modelcontextprotocol/servers-archived and was archived on 2025-05-28 with no commits since, while the npm package @modelcontextprotocol/server-gdrive stays published at 2025.1.14, so `npx @modelcontextprotocol/server-gdrive` still installs and runs without warning you. It is also much smaller than its reputation. The server exposes exactly one tool — `search`, which takes a query string and returns matching file names and MIME types. Everything else is MCP resources: files are addressed as `gdrive:///<file_id>`, with Google Workspace formats exported automatically (Docs to Markdown, Sheets to CSV, Presentations to plain text, Drawings to PNG) and all other file types served in their native format. Clients that do not surface resources well therefore look like the server is broken when it is behaving exactly as documented. Authentication is read-only by construction: the setup asks for the `https://www.googleapis.com/auth/drive.readonly` scope on an OAuth Client ID of type Desktop App, which means there is no tool here that can create, edit, move or reshare anything. The flow is manual — create a Google Cloud project, enable the Drive API, configure the consent screen, download the client key file, rename it to `gcp-oauth.keys.json` in the repo root, then run `node ./dist auth` once to write `.gdrive-server-credentials.json` beside it; a Docker path exists that mounts the key file and persists credentials in an `mcp-gdrive` volume. For maintained Drive access with writes, sharing controls and shared-drive support, the community server most teams move to is taylorwilsdon/google_workspace_mcp (PyPI `workspace-mcp`), which covers Drive as one of twelve Google Workspace services on a single connection. See the setup guide on this page for the full comparison.
The MCP server is free and open-source. Google Drive: 15GB free with Google account. Google One: from $1.99/mo (100GB). Workspace: from $7/user/mo.
dbx-mcp-server (amgadabdelhafez/dbx-mcp-server) is a community-built MCP server that gives AI assistants full read/write access to a Dropbox account through Dropbox's public API. Tools cover core file operations (list, upload, download, copy, move, and safe-delete with recycle-bin support so nothing is destroyed permanently), folder creation, metadata lookups, and content search across an account, letting a client answer "find my Q3 budget spreadsheet" or "move all screenshots from this month into an Archive folder" without a human digging through folders manually. Authentication uses OAuth 2.0 with PKCE: register a Scoped-Access app in the Dropbox App Console, grant the specific permission scopes needed (files.metadata.read, files.content.read/write, sharing.write, account_info.read), and supply `DROPBOX_APP_KEY`, `DROPBOX_APP_SECRET`, `DROPBOX_REDIRECT_URI`, and a `TOKEN_ENCRYPTION_KEY` for secure local token storage with automatic refresh. Install by cloning the repo, running `npm install && npm run build`, then `npm run setup` to complete the OAuth flow. Note this is not affiliated with or endorsed by Dropbox — Dropbox itself ships a separate, narrower official MCP server (dropbox/mcp-server-dash) scoped specifically to Dropbox Dash search and AI-assistant integration rather than general file management.
The MCP server is free and open-source. Dropbox: Basic (free, 2GB). Plus: $11.99/mo. Professional: $22/mo. Business: from $15/user/mo.
Microsoft MCP (elyxlz/microsoft-mcp) is a community-built MCP server that wraps the Microsoft Graph API to give AI assistants access to OneDrive files alongside Outlook mail, Calendar, and Contacts in a single unified integration — useful since most OneDrive usage happens inside the same Microsoft 365 account as email and scheduling. The file toolset covers list_files (paginated OneDrive browsing), get_file (download content), create_file (upload), update_file, delete_file, search_files, and a cross-surface unified_search tool that searches emails, events, and files together in one call, letting a client answer "find the contract I emailed myself last week" without knowing whether it lives in Mail or OneDrive. The server supports multiple simultaneous Microsoft accounts (personal, work, school) via list_accounts/authenticate_account/complete_authentication tools using device-code OAuth. Setup requires a free Azure App Registration (Microsoft Entra ID → App registrations, public client flow enabled) with delegated Files.ReadWrite, Mail.ReadWrite, Calendars.ReadWrite, Contacts.Read, and People.Read permissions, then an MICROSOFT_MCP_CLIENT_ID environment variable. Install via `uvx --from git+https://github.com/elyxlz/microsoft-mcp.git microsoft-mcp`, or `claude mcp add microsoft-mcp -e MICROSOFT_MCP_CLIENT_ID=your-app-id -- uvx --from git+https://github.com/elyxlz/microsoft-mcp.git microsoft-mcp` for one-line Claude Code setup. Not an official Microsoft release.
This MCP server is free and open-source. Check the GitHub repository for details.
Real User Monitoring data from Datadog.
The MCP server is free and open-source. Datadog RUM: From $1.50/1K sessions/mo. Session Replay: additional $1.80/1K sessions. 14-day free trial.
Frequently Asked Questions
What are the best alternatives to Excel MCP Server MCP Server?
The top alternatives to Excel MCP Server MCP Server in 2026 include Filesystem MCP Server, ClickHouse MCP Server, Sentry MCP Server, Datadog MCP Server, Grafana MCP Server. Each offers similar functionality in the Filesystem category with different features, pricing, and compatibility.
Is there a free alternative to Excel MCP Server MCP Server?
Yes, free alternatives to Excel MCP Server include Filesystem MCP Server, ClickHouse MCP Server, Sentry MCP Server. These offer free tiers or are completely open-source.
How do I choose between Excel MCP Server and its alternatives?
When choosing between Excel MCP Server and alternatives, consider: (1) Pricing — compare free tiers and paid plans, (2) Features — what specific capabilities you need, (3) Compatibility — which AI assistants (Claude, Cursor, VS Code) are supported, (4) Installation — npm, pip, docker, or other install methods.
Can I use multiple MCP servers at the same time?
Yes! MCP (Model Context Protocol) supports running multiple servers simultaneously. You can use Excel MCP Server alongside other MCP servers to extend your AI assistant's capabilities across different services and tools.