Best MCP Servers for Kilo Code (2026)

The best MCP servers for Kilo Code in 2026 are GitHub MCP Server for code, GitMCP for accurate docs, and Anyquery for local data — add those three first, then stop and check your tool budget. Kilo Code speaks the standard MCP protocol, so any of the servers in our directory work, but the ones worth wiring up are narrower than the marketing suggests. This is the opinionated shortlist: what to install, what to skip, and where the config actually lives.

Most MCP servers run locally over stdio — roughly 90% of them — which means Kilo Code spawns them as child processes on your machine. That matters for two reasons: they're fast, and their secrets never leave your laptop. The exceptions are hosted remote servers you reach over HTTP, which are easier to set up but hand your context to someone else's box.

Where Kilo Code keeps its MCP config

Kilo Code reads MCP servers from a JSON file, same shape as every other MCP client: a top-level mcpServers object keyed by server name. You edit it from the MCP panel in the extension, or by hand. A minimal stdio entry looks like this:

{
  "mcpServers": {
    "github": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"],
      "env": { "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_..." }
    }
  }
}

Global servers apply to every project; project-scoped ones live with the repo so your team inherits them. If you'd rather not hand-write JSON, our config generator emits a valid block per server. Keep tokens in env, not in args — args show up in process listings.

Start here: the three that earn their slot

Install these first because they cover the daily loop — code, docs, data — without bloating the tool list. Everything else is situational.

GitHub MCP Server is the anchor. It's GitHub's official server, so it tracks the API instead of lagging behind it, and it covers repos, issues, PRs, and Actions. Run it as local Docker (the config above) or point at GitHub's hosted remote if you don't want a container. The catch: it exposes a lot of tools, so use its toolset flags to enable only what you need.

GitMCP fixes the thing that makes coding agents lie. It's a free remote server that turns any GitHub repo into a live documentation source, so instead of hallucinating an API from training data, Kilo Code reads the current README and docs. Zero install — it's a URL. Point it at the repo of whatever library you're fighting with.

Anyquery runs SQL over your local files, databases, and 40+ apps — GitHub, Notion, Chrome, Todoist — and exposes them to Kilo Code over MCP. When you want the agent to answer "which of my open PRs touch this file" without a bespoke integration per source, this is the one query surface that reaches all of it. It's local, so nothing ships out.

Add these when the task calls for it

Reach for these only when a specific job needs them — each one costs tools you may not have. The mistake is installing all six on day one and drowning the model in options.

Octocode is for deep code research: GitHub, local filesystem, and LSP intelligence wired together so the agent can trace a symbol across repos like a staff engineer instead of grepping blind. It overlaps with GitHub MCP Server on the GitHub half, so pick one as your primary and don't run both unless you actually use the LSP features.

Package Registry MCP Server searches NPM, crates.io, NuGet, PyPI, and Go registries plus GitHub Security Advisories for current package info. Add it when you do a lot of dependency work and you're tired of the agent suggesting a version that was yanked two years ago.

Graphlit MCP Server ingests and runs RAG over Slack, Discord, Google Drive, Jira, and Linear. It's heavier than the rest and pulls in external context, so only add it if your work genuinely spans those tools — most solo devs won't need it.

The tool budget is the real constraint

The binding limit in Kilo Code isn't how many servers you can install — it's how many tools the model can reason over before it degrades. Practical clients hold up to around a 40-tool budget; past that, tool selection gets worse and latency climbs. This is the same math that bites Cursor users, and it's worth internalizing: see the tool-limit math for the full breakdown.

One server can expose 30+ tools on its own. Two or three enabled naively will blow the budget, and the symptom is subtle — the agent starts picking the wrong tool or ignoring a server entirely.

Server	Scope	Transport	Add when
GitHub MCP Server	Repos, issues, PRs, Actions	Local Docker or remote	Always — anchor server
GitMCP	Live repo docs	Remote (URL)	You hit doc hallucinations
Anyquery	SQL over files + 40+ apps	Local stdio	You query mixed data sources
Octocode	Code research + LSP	Local	Cross-repo symbol tracing
Package Registry MCP	Registry + advisory search	Local	Heavy dependency work
Graphlit MCP	RAG over Slack/Jira/etc.	Remote/hosted	Work spans those apps

Default: enable GitHub MCP Server, GitMCP, and Anyquery, then trim each server's tools to the handful you use. Add the other three per-project, not globally. For the shortlist behind agentic workflows generally, see the coding-agents picks.

What to skip

Skip anything that duplicates a server you already have, and skip remote servers for anything sensitive. Running both GitHub MCP Server and Octocode against GitHub is redundant tool bloat — choose one primary. Skip Graphlit unless you actually live in Slack and Jira; the RAG overhead isn't free.

Also skip the instinct to install broadly "to be safe." Every enabled tool competes for the model's attention, and an unused server is pure cost. Fewer, well-scoped servers beat a full panel every time.