Compatible with every major AI agent and IDE
What is the Hashnode MCP Server?
Connect your Hashnode account to any AI agent to streamline your technical writing and blogging workflow. This MCP server allows you to interact with the Hashnode GraphQL API through natural language.
What you can do
- User Profiles — Retrieve detailed information about any Hashnode user by their handle using
get_user. - Publication Management — List all posts from a specific publication using its domain or hostname with
get_publication_posts. - Content Retrieval — Fetch full post content and metadata using slugs and hostnames via
get_post. - Publishing — Create and publish new blog posts with Markdown support and custom tags using
create_postdirectly from your conversation. - Editing — Update existing posts, titles, and content with
update_postwithout leaving your AI interface.
How it works
- Subscribe to this server
- Enter your Hashnode Personal Access Token
- Start managing your technical blog from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Technical Writers — Draft and publish articles directly from your AI-assisted writing environment.
- Developers — Share knowledge and updates on your Hashnode blog without switching contexts.
- Content Managers — Monitor publication feeds and update existing posts efficiently.
Built-in capabilities (5)
Publish a new post to a publication
Get a single post by its slug
Get a list of posts from a specific publication
Get details about a specific Hashnode user
Modify an existing post
Why CrewAI?
When paired with CrewAI, Hashnode becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Hashnode tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
- —
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Hashnode in CrewAI
Hashnode and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Hashnode to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Hashnode in CrewAI
The Hashnode MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 5 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Hashnode for CrewAI
Every tool call from CrewAI to the Hashnode MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I fetch profile details for any Hashnode user?
Yes! Use the get_user tool with the specific username handle. The agent will return their profile information, bio, and social links.
Does the publishing tool support Markdown formatting?
Absolutely. Both create_post and update_post accept contentMarkdown, allowing you to publish rich technical content with code blocks, headers, and links.
How do I list posts from a specific blog domain?
Use the get_publication_posts tool and provide the host domain (e.g., 'engineering.hashnode.dev' or your custom domain). It will return a list of recent posts from that publication.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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