OpenObserve MCP server
by alilxxeyLet your AI search your OpenObserve logs, traces, dashboards and stream schemas for you.
AI Library · 4,609 MCP servers
Let your AI search your OpenObserve logs, traces, dashboards and stream schemas for you.
Put one simple rules file between your AI and its tools, so risky actions get blocked or flagged before they happen.
Give your AI a memory tree of your project's decisions, so it knows why the work is where it is.
Lets your AI look at your Kubernetes or OpenShift cluster, check pods and logs, and make changes when you ask.
Ask your AI about your LLM costs, errors, latency and alerts, and let it adjust alerts for you.
Keep a tamper-proof record of every tool call your AI makes, so you can check what it really did.
Give your AI a long-term memory of your project so it remembers decisions and reasons between chats.
Ask your AI to run Terraform plans, apply changes and check your cloud infrastructure in plain words.
Lets your AI run SQL queries and inspect tables in a local DuckDB database file.
Adds a safety layer between your AI and its tools, logging every action and blocking risky ones.
Give your AI a long-term memory for your project, so it remembers past work between sessions.
Lets your AI publish a small website to decentralized storage and hand you back a live link.
Lets your AI look inside a DolphinDB database and run queries for you in plain chat.
Lets your AI check your MCP config files for risky settings and explain what it finds.
Give your AI a long-term memory that keeps what matters and lets the rest fade.
Lets your AI read Edge Delta logs, anomalies and pipelines, and safely test or deploy pipeline changes for you.
Let your AI look inside your database, explain its tables, and run SQL queries for you.
Let your AI keep a signed, checkable record of what it was allowed to do and what it actually did.
Give your coding AI a shared memory that stays tidy, with old notes replaced instead of piling up.
Lets your AI find cloud and SaaS resources in Firefly and turn them into infrastructure code.
Let your AI look up AgentGuard traces, alerts, usage, costs and budget health.
Your AI checks risky actions before doing them, and asks you first when something looks dangerous.
Your AI remembers what it decided, what it rejected and why, so old choices can be revisited.
Publish a file or website from your AI chat and get back a live public web link.