Anchord

Hosted API-backed.This MCP server is a thin proxy to the Anchord SaaS platform. All scoring, matching, validation, and data persistence happen server-side. No business logic runs locally.

Read-only by design.Anchord never writes to your external systems (CRMs, databases, etc.).guard_writeevaluates a proposed write and returns allowed/blocked — the caller decides whether to proceed.

ANCHORD_API_KEY=<YOUR_ANCHORD_API_KEY> npx -y @anchord/mcp-server

That's it. The server starts over stdio and is ready for MCP clients.

3. Or connect to the hosted remote (zero install)

No local install needed. Point any MCP client that supports remote HTTP transport at the hosted endpoint:

{ "mcpServers": { "anchord": { "url": "https://mcp.anchord.ai/mcp", "headers": { "Authorization": "Bearer <YOUR_ANCHORD_API_KEY>" } } } }

Add to.cursor/mcp.json(workspace) or~/.cursor/mcp.json(global):

Remote MCP (for clients that support HTTP transport)

For zero-install remote access, use the hosted endpoint instead of a local stdio process. This works with any MCP client that supports theurl+headersconfiguration format:

{ "mcpServers": { "anchord": { "url": "https://mcp.anchord.ai/mcp", "headers": { "Authorization": "Bearer <YOUR_ANCHORD_API_KEY>" } } } }

docker build -t anchord-mcp . echo '{"jsonrpc":"2.0","id":1,"method":"initialize",...}' | \ docker run --rm -i -e ANCHORD_API_KEY=<YOUR_ANCHORD_API_KEY> anchord-mcp

Or use the compose file for local testing:

cp examples/env.example .env # Edit .env with your API key docker compose up

The recommended sequence for agents writing to external systems:

1. ingest_record Push the source record into Anchord (optional if using OAuth integrations) 2. resolve_company Match to a canonical AnchorID or resolve_person → status: resolved | not_found | needs_review 3. IF needs_review STOP. Do not write. Surface candidates to the user. Direct them to the Review Queue. 4. guard_write Evaluate the proposed write → allowed: true | false (with block codes) 5. IF allowed The agent performs the external write. Anchord never writes. 6. Log request_id Every response includes a request_id for audit trail and debugging.

Useget_entityorget_entity_exportat any point to inspect AnchorID details or retrieve the merged golden record.

Onlyresolve_returnsneeds_review. It means Anchord found multiple plausible matches and cannot auto-resolve with confidence.
- Do not write.The data is ambiguous.
- Surface the candidatesto the user — the response includes entity IDs and match scores.
- Direct the user to the Review Queue:https://app.anchord.ai/app/queues/needs-review
- Retry later.Once a human resolves the ambiguity, subsequent resolve calls returnresolved.

Whenresolve_returnsneeds_review, it means multiple candidate AnchorIDs matched with similar confidence. The agent should stop, surface the candidates to a human, and direct them to the Anchord Review Queue. Once resolved, subsequent calls returnresolved.

Navigate your Aiven projects and interact with the PostgreSQL®, Apache Kafka®, ClickHouse® and OpenSearch® services

Yunxiao MCP Server provides AI assistants with the ability to interact with the Yunxiao platform.

Get prescriptive CDK advice, explain CDK Nag rules, check suppressions, generate Bedrock Agent schemas, and discover AWS Solutions Constructs patterns.

This AWS Labs Model Context Protocol (MCP) server for CloudTrail enables your AI agents to query AWS account activity for security investigations, compliance auditing, and operational troubleshooting.

Core AWS MCP server providing prompt understanding and server management capabilities.

Analyze CDK projects to identify AWS services used and get pricing information from AWS pricing webpages and API.

Query and analyze your Axiom logs, traces, and all other event data in natural language

Manage and interact with Microsoft Azure services.

Bastion: External Attack Surface Monitoring

Ask your AI assistant about your attack surface: run scans, catch expiring certificates and domains, triage findings, and generate reports.