Datadog documents a remote Model Context Protocol server at docs.datadoghq.com/bits_ai/mcp_server that connects AI agents in Cursor, Claude Code, Codex CLI, VS Code, Gemini CLI, and other MCP clients to observability data across APM, logs, metrics, monitors, dashboards, and security signals. Setup guides describe OAuth-based connection to Datadog's hosted MCP endpoint (distinct from the local-only Code Security MCP Server used for SAST/SCA scans). Fair-use limits listed in docs include 50 requests per 10 seconds burst and 50,000 monthly tool calls; Audit Trail records MCP actions with tool name, arguments, user identity, and client, while metrics `datadog.mcp.session.starts` and `datadog.mcp.tool.usage` tag usage by client and tool.
Use cases
- Let coding agents query live production traces and logs while debugging incidents
- Pull monitor and dashboard context into Claude Code or Cursor without leaving the IDE
- Audit MCP tool usage through Datadog Audit Trail event name `MCP Server`
- Enable specific toolsets per setup docs when teams want narrower agent permissions
- Pair with the Datadog Cursor extension workflows referenced in Datadog engineering blogs
Key features
- Cursor
- Claude Code
- Claude Desktop
- VS Code
- Codex CLI
- Gemini CLI
- GitHub Copilot
Frequently Asked Questions
- Is this the Code Security MCP Server?
- No—Datadog docs distinguish this remote observability MCP from the local Code Security MCP used for SAST/SCA/IaC scans.
- What are the documented rate limits?
- Docs list 50 requests per 10 seconds burst and 50,000 monthly tool calls, subject to change via Datadog support.
- Is GovCloud supported?
- Documentation states the Datadog MCP Server is not GovCloud compatible.
Related
Related
3 Indexed items
PostHog MCP Server
PostHog documents a free hosted Model Context Protocol endpoint at `https://mcp.posthog.com/mcp` per posthog.com/docs/model-context-protocol that lets MCP clients query analytics, manage feature flags, investigate errors, run HogQL, triage support workflows, and configure CDP destinations from natural-language prompts. The PostHog Wizard installs the server into Cursor, Claude Code, Claude Desktop, Codex, VS Code, Windsurf, and Zed via `npx @posthog/wizard@latest mcp add`. Authentication routes to the correct US or EU data region; manual setups can pass a personal API key with the MCP Server preset through `mcp-remote` and an `Authorization` Bearer header. Source lives in the PostHog monorepo at `services/mcp` (the standalone PostHog/mcp repository redirects there).
Weights & Biases MCP Server
Weights & Biases documents a hosted Model Context Protocol server at `https://mcp.withwandb.com/mcp` (recommended) and an open-source `wandb/wandb-mcp-server` package for local stdio or HTTP per docs.wandb.ai/platform/mcp-server. Authenticated clients pass a W&B API key in the `Authorization: Bearer` header. Documented tools include `query_wandb_tool` and `get_run_history_tool` for experiment metrics, `query_weave_traces_tool` and `count_weave_traces_tool` for LLM traces, `create_wandb_report_tool` for markdown reports, `search_wandb_docs_tool` for docs.wandb.ai, and `query_wandb_entity_projects` for project listings. Dedicated/on-prem deployments can set `WANDB_BASE_URL` with the local server per README.
LangSmith MCP Server
LangChain documents a LangSmith Model Context Protocol server that lets MCP clients read conversation threads, prompts, runs and traces, datasets, experiments, and billing usage from a LangSmith workspace. For LangSmith Cloud, docs recommend the OAuth-authenticated LangSmith Remote MCP (regional endpoints on api.smith.langchain.com and documented EU/APAC/AWS variants) with the same tool surface and no separate deployment. The standalone HTTP server at https://langsmith-mcp-server.onrender.com/mcp remains documented for API-key access via the LANGSMITH-API-KEY header, while self-hosted LangSmith users can run the open-source langsmith-mcp-server package with uvx, Docker HTTP on port 8000, or point LANGSMITH_ENDPOINT at private instances. Tools include get_thread_history, list_prompts, fetch_runs (with FQL filters and character-budget pagination), dataset/example readers, list_experiments, and get_billing_usage per the official tool table.