kodekloud-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| KODEKLOUD_USE_MOCK | No | Set to 'true' to enable offline mock mode. Set to 'false' for live mode. Default is 'true'. | true |
| KODEKLOUD_SESSION_COOKIE | Yes | Your KodeKloud session cookie or Bearer JWT token for authentication. Required for live mode (when KODEKLOUD_USE_MOCK is false). | |
| KODEKLOUD_CACHE_TTL_SECONDS | No | Cache time-to-live in seconds for API responses. Default is 60. | 60 |
| KODEKLOUD_ENABLE_WRITE_TOOLS | No | Set to 'true' to enable write tools (start_lab, stop_lab). Default is 'false'. | false |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_course_progressA | Get completion percentage, completed vs total labs, and last activity. Fetches overall progress metrics across all enrolled courses or filters specifically for a given course name or ID (e.g. 'CKA' or 'Kubernetes'). Args: course_name: Optional course title or slug to filter progress for. If omitted, returns progress for all enrolled courses. Returns: CourseProgressResponse with completion percentages and lab counts. |
| list_enrolled_coursesA | List all courses the user is currently enrolled in on KodeKloud. Returns titles, categories (Kubernetes, Cloud, Linux, IaC), difficulty levels, and current enrollment status (In Progress, Completed, Not Started). Returns: EnrolledCoursesResponse containing the list of enrolled courses. |
| get_course_outlineA | Retrieve course modules, lessons, and labs with completion status. Provides a detailed syllabus breakdown showing which lectures and hands-on labs have been completed, and indicates the next suggested lesson to help the learner identify exactly what to study next. Args: course_name: Title, slug, or ID of the course (e.g. 'CKA', 'Docker'). Returns: CourseOutlineResponse with modules, lessons, and next suggested item. |
| get_active_labsB | List active interactive hands-on labs with status and remaining lease time. Inspects currently provisioned or running lab sessions (Running, Paused, Stopped), remaining time before automatic expiration, and access URLs. Returns: ActiveLabsResponse with active lab session details. |
| get_certificationsB | Track active certification paths, mock exams, and exam readiness scores. Provides exam preparation progress for certifications like CKA, CKAD, CKS, HashiCorp Terraform Associate, and AWS, including mock exam completion rates and target exam dates. Returns: CertificationsResponse with tracked certifications and readiness. |
| get_learning_summaryA | Get a compact digest of learning streaks, recent activity, and study stats. Designed specifically for constructing personalized study schedules. Includes current consecutive study streak in days, total hours learned, recent activity history, count of pending labs, and next suggested lesson. Returns: LearningSummaryResponse compact learner profile digest. |
| get_engineer_taskA | Fetch the current active assigned task/ticket on KodeKloud Engineer. Retrieves the active ticket scenario (SysAdmin, DevOps, Cloud, Kubernetes), including task description, acceptance criteria, target servers (e.g. stapp01, jump_host), assigned credentials/usernames, points, and remaining deadline hours. Returns: EngineerTaskResponse with active task details or empty notification. |
| get_engineer_profileA | Retrieve user profile, career track level, XP, and rank on KodeKloud Engineer. Returns current engineering role (e.g. 'DevOps Engineer', 'System Administrator'), total points/XP, global leaderboard rank, tasks completed, tasks failed, success rate, and promotion eligibility. Returns: EngineerProfileResponse with standing and career metrics. |
| list_engineer_historyA | List historical tasks, tickets, and results on KodeKloud Engineer. Inspects past completed, failed, or expired tasks, tracks, points awarded, and completion timestamps. Args: limit: Maximum number of historical task records to return (default: 10). status: Optional filter by status: 'Success', 'Failed', or 'Expired'. Returns: EngineerHistoryResponse with historical task records. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| study_plan | Generate a personalized, milestone-driven KodeKloud study plan. Instructs the AI assistant to inspect the learner's progress across courses, certifications, outlines, and active labs, and produce a structured weekly plan. Args: goal: The learner's target goal (e.g. 'CKA in 8 weeks', 'Terraform in 1 month'). |
| troubleshoot_engineer_task | Act as a Senior DevOps Tech Lead to guide troubleshooting for an active Engineer task. Instructs the AI assistant to inspect the current assigned KodeKloud Engineer ticket via get_engineer_task and guide the learner through investigative steps without giving away the complete solution directly. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Most tools have clearly distinct purposes: course progress, outline, enrolled courses, active labs, certifications, learning summary, and engineer-specific resources. However, get_course_progress, get_course_outline, and get_learning_summary all touch on course completion and next-lesson guidance, creating mild overlap. Descriptions help differentiate them, so misselection is unlikely but possible.
All tool names follow a consistent snake_case verb_noun pattern using get_ or list_. The convention is predictable throughout, with no mixing of styles or vague verbs. This makes the tool set easy to scan and understand.
Nine tools is well within the ideal range for a focused learning-platform MCP. Each tool covers a distinct area: courses, progress, labs, certifications, summaries, and KodeKloud Engineer tasks. No tool feels redundant or excessive for the scope.
The surface covers the main read-only areas learners care about: enrolled courses, progress, outlines, labs, certifications, study summaries, and engineer tasks/profile/history. Minor gaps exist around lab session control (e.g., starting or stopping labs) and task submission actions, but core monitoring and discovery workflows are well supported.