"OnePageCRM - A Simple Action-Focused CRM Software" matching MCP servers:

Enables recording agent proposals, executions, redactions and annotations into an append-only, hash-linked evidence chain, then exporting a self-contained range and verifying offline from the export's own bytes alone so a third party can check history without trusting the agent runtime or its storage.

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

Enables external agents to delegate real-world actions to Hermes Agent via MCP tools such as hermes_run and hermes_plan.

A transparent proxy that intercepts high-risk tool calls and requires OTP-based human approval before they can be executed. It acts as a configurable circuit breaker between AI agents and target MCP servers to prevent unauthorized or dangerous actions.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

MCP server that gates agent tool calls by normalizing intent, denying unknown/unattended destructive actions, and requiring HITL prove approval for high-risk operations. It maintains an append-only hash-chained Action Ledger and exposes gate_check and ledger_verify tools without ever executing tools.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables an AI agent to preflight concrete tool calls by recording principal, destination, scope, authority evidence, and relations, allowing only formed actions to execute and producing inspectable evidence receipts.

Wraps the Close CRM API to enable AI agents to interact with Close CRM data, manage leads, contacts, and activities through natural language.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

A paid remote MCP server that issues and checks structured action receipts, with audit logs and reviewer-ready evidence for WebMCP actions.

Enables AI agents to manage Dashan CRM (customers, orders, products, etc.) via MCP with built-in safety constraints.

Enables AI sales agents to interact with a CRM via event-sourced actions, identity resolution, guard checks, and an approval inbox, managing communications and tasks while adhering to compliance rules.

Enables autonomous browser action planning by mapping goals into resilient selector action sequences, with deterministic execution and structured telemetry through MCP.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

A foundation for creating custom Model Context Protocol servers that can integrate with AI systems, providing a simple BMI calculator tool as an example implementation.

Enables MCP-compatible agents to arbitrate typed state-action schemas, dispatch routine actions deterministically, and apply pre-escalation filters that reduce unnecessary frontier LLM calls. It supports low-latency, schema-enforced routing with safety guardrails and local-first memory retention.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

Enables AI agents and MCP clients to translate high-level web automation goals into deterministic, resilient browser selector action sequences. It runs as a zero-dependency Python MCP server that returns structured execution plans and telemetry for agentic workflows.