Which integrations are available for this server?

Enables CRM synchronization for leads and companies, allowing workflow results and scoring history to be stored in the knowledge base. Provides high-quality text-to-speech capabilities as a modular step within media production and content automation workflows. Supports CRM data synchronization and sales automation, including lead enrichment and tracking ICP scoring history. Provides specialized tools to preview and import existing n8n workflows, converting them into AI-native Agentled workflows. Integrates OpenAI's intelligence, including GPT models for reasoning and DALL-E for automated image generation.

@agentled/mcp-server

The automation engine built for AI agents. Intelligent AI workflow orchestration with long-term memory, 100+ integrations, and unified credits.

npm version license

Agentled Server MCP server

What is Agentled?

Agentled is the automation engine built for AI agents. It gives Claude, Codex, Cursor, Windsurf, and any MCP-compatible client direct access to intelligent workflow orchestration, long-term memory, and 100+ integrations.

Three things make it different:

🧠 Long-Term Memory — A built-in Knowledge Graph stores insights across workflow executions. Your agents get smarter over time — they remember past research, lead scores, content performance, and business context.

⚡ Unified Credits — One API key, one credit system, 100+ services. No need to sign up for LinkedIn, email, scraping, AI models, or video generation separately. Connect once, use everything.

🎯 Intelligent Orchestration — AI reasons at every step. Workflows aren't just "if this then that" — they understand context, make decisions, and adapt to results.

See it in action

$ agentled create "Outbound to fintech CTOs in Europe"

Loading workspace context from Knowledge Graph...
✦ ICP loaded  ✦ 3 prior campaigns  ✦ 847 contacts in KG

Creating campaign with 3 workflows...

━━ Workflow 1: Prospect Research  linkedin · hunter · clearbit
  ✓ LinkedIn: CTO + fintech + EU → 189 profiles
  ✓ Enriched via Hunter + Clearbit → 156 matched
  ✓ ICP scoring → 43 high-intent leads

━━ Workflow 2: Signal Detection  web-scraper · crunchbase
  ✓ Job postings → 12 hiring devops
  ✓ Crunchbase → 8 recently funded
  ✓ Cross-match: hiring + funded → 5 hot leads

━━ Workflow 3: Outreach  email · linkedin · kg
  ✓ Personalized emails from context
  ✓ LinkedIn requests with custom notes
  ✓ 43 leads saved to Knowledge Graph

Campaign saved. Scheduled: every 48h
Credits used: 720
→ https://www.agentled.app/your-team/fintech-cto-outbound

One prompt. Three workflows. LinkedIn enrichment, email finding, AI scoring, multi-channel outreach — all orchestrated, all stored in the Knowledge Graph for the next run.

Quick Start

claude mcp add agentled \
  -e AGENTLED_API_KEY=wsk_... \
  -- npx -y @agentled/mcp-server

Local development

Use the local built entrypoint when you want to test unpublished changes against a local app. npx -y @agentled/mcp-server always uses the latest published npm package.

cd agentled-mcp-server
npm run build

claude mcp add --transport stdio agentled_local \
  --env AGENTLED_API_KEY=wsk_... \
  --env AGENTLED_URL=http://localhost:8080 \
  -- node /absolute/path/to/agentsled-front/agentled-mcp-server/dist/index.js

Getting your API key

Sign up at agentled.app
Open Workspace Settings > Developer
Generate a new API key (starts with wsk_)

Why Agentled MCP?

One API Key. One Credit System. 100+ Services.

No need to sign up for LinkedIn APIs, email services, web scrapers, video generators, or AI models separately. Agentled handles all integrations through a single credit system.

Capability	Credits	Without Agentled
LinkedIn company enrichment	50	LinkedIn API ($99/mo+)
Email finding & verification	5	Hunter.io ($49/mo)
AI analysis (Claude/GPT/Gemini)	10-30	Multiple API keys + billing
Web scraping	3-10	Apify account ($49/mo+)
Image generation	30	DALL-E/Midjourney subscription
Video generation (8s scene)	300	RunwayML ($15/mo+)
Text-to-speech	60	ElevenLabs ($22/mo+)
Knowledge Graph storage	1-2	Custom infrastructure
CRM sync (Affinity, HubSpot)	5-10	CRM API + middleware

Workflows That Learn

Other automation tools start from zero every run. Agentled's Knowledge Graph remembers across executions — what worked, what didn't, what humans corrected. Every run compounds on the last.

Run 1:  Investor scoring → 62% accuracy (cold start)
Run 5:  → 78% (learning from IC feedback)
Run 12: → 89% (compound learning from outcomes, zero manual tuning)

Intelligent Orchestration

Unlike trigger-action tools, Agentled workflows have AI reasoning at every step. Multi-model support (Claude, GPT-4, Gemini, Mistral, DeepSeek, Moonshot), adaptive execution, and human-in-the-loop approval gates when needed.

What Can You Build?

Lead Enrichment & Sales Automation

"Find fintech CTOs in Europe, enrich via LinkedIn + Hunter, score by ICP fit,
draft personalized outreach, save everything to the Knowledge Graph"

Content & Media Production

"Scrape trending topics in our niche, generate 5 LinkedIn posts with AI,
create thumbnail images, schedule publishing for the week"

Company Research & Intelligence

"Research this company from its URL — team, funding, market position, competitors.
Generate an investment memo. Store in KG for future reference."

VC Investor Matching (real case study)

"Match this startup against our 2,000+ investor database. Score by sector focus,
stage preference, check size, and portfolio synergy. Compare with last round's outcomes."

3,000+ profiles processed. IC-ready reports. Prediction vs outcome learning — accuracy went from 62% to 89% over 12 runs with zero manual tuning.

Built-in Capabilities

Media Production: Video generation, image generation, text-to-speech, auto-captions, media assembly

AI Intelligence: Multi-model AI (Claude, GPT-4, Gemini, Mistral, DeepSeek, Moonshot, xAI), Knowledge Graph, feedback loops, scoring & analytics

Data & Integration: LinkedIn (search, enrich, post), email (send, personalize), web scraping, social publishing, CRM sync, document analysis, OCR

Available Tools

Workflows

Tool	Description
`list_workflows`	List all workflows in the workspace
`get_workflow`	Get full workflow definition by ID
`create_workflow`	Create a new workflow from pipeline JSON
`update_workflow`	Update an existing workflow
`add_step`	Add a step with automatic positioning and next-pointer rewiring
`update_step`	Deep-merge updates into a single step by ID
`remove_step`	Remove a step with automatic next-pointer rewiring
`delete_workflow`	Permanently delete a workflow
`validate_workflow`	Validate pipeline structure, returns errors per step
`publish_workflow`	Change workflow status (draft, live, paused, archived)
`export_workflow`	Export a workflow as portable JSON
`import_workflow`	Import a workflow from exported JSON

Drafts & Snapshots

Tool	Description
`get_draft`	Get the current draft version of a workflow
`promote_draft`	Promote a draft to the live version
`discard_draft`	Discard the current draft
`create_snapshot`	Create a manual config snapshot
`delete_snapshot`	Delete a specific config snapshot
`list_snapshots`	List version snapshots for a workflow
`restore_snapshot`	Restore a workflow to a previous snapshot

Executions

Tool	Description
`start_workflow`	Start a workflow execution with input. Pass `useMocks: false` to force a real (credit-consuming) run that ignores per-step mock data; defaults to honoring the workflow's configured mocks.
`list_executions`	List executions for a workflow (paginated via `nextToken`)
`get_execution`	Get execution details with step results
`list_timelines`	List step execution records (timelines) for an execution (paginated via `nextToken`)
`get_timeline`	Get a single timeline by ID with full step output
`stop_execution`	Stop a running execution
`retry_execution`	Retry a failed step — auto-detects the most recent failure if no timeline ID provided

Apps & Testing

Tool	Description
`list_apps`	List available apps and integrations
`get_app_actions`	Get action schemas for an app
`test_app_action`	Test an app action without creating a workflow
`test_ai_action`	Test an AI prompt without creating a workflow
`test_code_action`	Test JavaScript code in the same sandboxed VM as production
`get_step_schema`	Get allowed PipelineStep fields grouped by category

Knowledge & Data

Tool	Description
`get_workspace`	Get workspace info and settings
`get_workspace_company_profile`	Get the editable workspace company profile and offerings
`update_workspace_company_profile`	Update top-level company profile fields like name, URLs, logo, industry, size, and additional information
`upsert_workspace_company_offerings`	Create new offerings or update existing offerings in the workspace company profile
`list_knowledge_lists`	List knowledge lists in the workspace
`get_knowledge_rows`	Get rows from a knowledge list
`get_knowledge_text`	Get text content from a knowledge entry
`create_knowledge_list`	Create a new knowledge list with a typed schema (idempotent on key collision)
`update_knowledge_list_schema`	Add or remove fields on an existing list schema
`delete_knowledge_list`	Permanently delete a list and all its rows
`upsert_knowledge_rows`	Insert or update rows in a list (max 500/call, per-row error reporting)
`delete_knowledge_rows`	Delete rows by ID
`upsert_knowledge_text`	Create or update a text knowledge entry
`delete_knowledge_text`	Delete a text knowledge entry by key
`query_kg_edges`	Query knowledge graph edges
`get_scoring_history`	Get scoring history for an entity

Branding (Whitelabel)

Tool	Description
`get_branding`	Get the workspace's whitelabel branding config (displayName, logo, colors, favicon, badge)
`update_branding`	Update branding — set displayName, logoUrl, tagline, primaryColor, primaryColorDark, faviconUrl, hideBadge

Conversational Agent

Tool	Description
`chat`	Send a message to the AgentLed AI agent. Build workflows through natural language — no JSON required. Supports multi-turn conversations via session_id.

Intent Router

Tool	Description
`do`	Natural language intent router — describe what you want and it auto-selects and executes the right tool

Coming from n8n?

Import existing n8n workflows and make them AI-native:

Tool	Description
`preview_n8n_import`	Preview an n8n workflow import (dry run)
`import_n8n_workflow`	Import an n8n workflow into Agentled

For Agencies: White-Label Ready

Build workflows once, deploy to multiple clients under your own brand. Configure branding directly from the MCP server:

"Set my workspace branding: displayName 'Acme AI', primaryColor '#6366f1', tagline 'Powered by Acme'"

Use get_branding and update_branding to manage displayName, logo, colors, favicon, tagline, and badge visibility. Client portal appearance updates instantly.

Persistent Memory — Examples

Memories let workflows learn across executions. Store what worked, recall it next time.

Store a fact after enrichment

"Store a memory: key 'icp_criteria', value { industry: 'fintech', minEmployees: 50, region: 'EU' },
category 'preference', scope 'workspace'"

Recall before scoring

"Recall memory 'icp_criteria' at workspace scope — use it to score this batch of leads"

Search for past outcomes

"Search memories for 'conversion rate' in the 'outcome' category"

Track a running metric

"Store memory: key 'total_leads_processed', value 43, merge 'increment', scope 'workspace'"

Each subsequent call with merge: 'increment' adds to the existing value — no read-modify-write needed.

Proactive Agents — Examples

Proactive agents are background monitors that autonomously trigger workflows when conditions are met.

Create an agent that watches for new leads

"Create a proactive agent named 'New Lead Watcher' that checks the 'incoming-leads' knowledge list
every 5 minutes. When new rows appear, start the 'lead-enrichment' workflow with the new rows as input.
Limit to 10 actions per day."

Config structure:

{
  "monitorInterval": "5m",
  "evaluation": { "mode": "rules" },
  "monitors": [{
    "type": "kg_list",
    "listKey": "incoming-leads",
    "condition": "new_rows"
  }],
  "actions": [{
    "type": "start_workflow",
    "workflowId": "wf_abc123",
    "inputMapping": { "leads": "{{monitor.newRows}}" }
  }],
  "maxActionsPerDay": 10,
  "cooldownMs": 300000
}

Create an AI-evaluated agent

"Create a proactive agent that checks execution history every hour.
Use AI evaluation to decide if the failure rate is abnormal, then notify me via email."

{
  "monitorInterval": "1h",
  "evaluation": { "mode": "ai", "modelTier": "mini", "maxCreditsPerDay": 50 },
  "monitors": [{
    "type": "execution_history",
    "condition": "consecutive_failures",
    "threshold": 3
  }],
  "actions": [{
    "type": "notify",
    "channel": "email",
    "message": "{{monitor.summary}}"
  }],
  "maxActionsPerDay": 5
}

Pause and resume

"Pause proactive agent pa_xyz789"
"Resume proactive agent pa_xyz789"

Works With

Claude Code (Anthropic)
Codex (OpenAI)
Cursor
Windsurf
Any MCP-compatible client

Building from Source

git clone https://github.com/Agentled/mcp-server.git
cd mcp-server
npm install
npm run build

License

MIT