A production-oriented MCP runtime that bridges Claude and Cursor with the Laviya AI orchestration platform. Exposes eight tools for task management and execution tracking: feed tasks, check work status, cancel jobs, add comments, retrieve your work queue, and report token usage. Operates on a global runtime with project-local config model using `.laviya/project.json` files in your repository. Ships with reusable prompt assets, Cursor rules, and Claude skills bundled in an npm package you can import directly. Useful when you need structured orchestration workflows with validation, retries, and idempotency guarantees built into your agent interactions. All responses come back as structured JSON envelopes with failure flags and message arrays.
Laviya Agent Skills is a repository of reusable orchestration assets for IDE and agent integrations. It provides a production-oriented MCP runtime, shared orchestration prompt assets, and client-specific artifacts for tools such as Cursor and Claude.
laviya-agent-skills: reusable prompt, rule, and skill asset bundle for Node-based toolinglaviya-mcp-server: stdio MCP runtime published from mcp/core/: shared orchestration prompt assetsmcp/: TypeScript MCP runtime scaffold (laviya-mcp-server)cursor/: Cursor rule artifactsclaude/: Claude skill artifactsdocs/: setup, npm publishing, and end-user onboarding guideslaviya-agent-skills/
core/
mcp/
src/
examples/
README.md
cursor/
claude/
docs/
Setup.md
MCPServerPublish.md
InstallationAndUsage.md
cd mcp
npm install
npm run typecheck
npm run build
npm run dev
Required environment variable:
LAVIYA_API_KEYInstall the reusable asset bundle:
npm install laviya-agent-skills
Example usage:
import { assets, resolveAssetPath } from "laviya-agent-skills";
import { readFileSync } from "node:fs";
const cursorRule = readFileSync(assets.cursorRule, "utf8");
const orchestratorPrompt = readFileSync(resolveAssetPath("orchestratorSystemPrompt"), "utf8");
mcp/README.mddocs/Setup.mddocs/MCPServerPublish.mddocs/InstallationAndUsage.mddocs/InstallationAndUsage.mdThe MCP runtime follows a global-runtime plus project-local-config model:
.laviya/project.json or .laviya.json)Current MCP tool set includes both orchestration and local-direct task feed flows:
laviya_helplaviya_feed_tasklaviya_get_local_work_statuslaviya_cancel_local_worklaviya_add_task_commentlaviya_get_my_worklaviya_start_executionlaviya_complete_executionlaviya_report_token_usagelaviya_diagnosticsAll tools return API envelope JSON text in the shape: { HasFailed, Messages, Data }.
Work items may include a backend-defined ExecutionPolicy. Analysis and review
policies are read-only: agents must not implement changes, and enforced policies
require matching completion executionEvidence and summary policyCompliance.
For full architecture details and file-level scaffolding, refer to mcp/README.md.
LAVIYA_API_KEY*secretLaviya API key used for MCP runtime authentication.
LAVIYA_BASE_URLOptional base URL override for the Laviya API endpoint.
LAVIYA_AGENT_UIDOptional agent UID override for execution orchestration.
LAVIYA_LOG_LEVELOptional log level override (debug|info|warn|error).
LAVIYA_GLOBAL_CONFIG_PATHOptional path override for global runtime config (useful in sandboxed environments where home directory is not readable).
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent