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166 posts about MCP. Every summary links to the original.
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An agentic ad stack wires governed customer signals to campaign execution through a shared tool interface and server-side guardrails. The diagram shows each layer, the direction of a tool call, and where control stays human.
A four-stage flow showing how a coding agent moves from a task to a reviewed change by grounding on verified skills, live system state, and code-first config before it acts.
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S&P Global Energy aimed to make its structured data estate—spanning LNG, Chemicals, Crude Oil, and other commodities—conversationally accessible via AI agents. The team evaluated approaches and chose Databricks Genie Agents, where subject matter experts curate one agent per dataset group without writing code. Each Genie Agent is automatically exposed as a managed MCP server, providing a governed, zero-deployment integration point. A FastMCP-based proxy composes multiple Genie MCP servers into composite endpoints for cross-domain questions. This architecture shortened time to market from months to days, with governance via Unity Catalog and an open MCP standard enabling both internal and external consumers.
Most enterprise REST APIs are invisible to AI agents, forcing teams to run separate MCP servers that duplicate their existing gateway logic. Google Cloud API Gateway in Public Preview solves this by acting as a remote MCP server — annotate the OpenAPI 3.0.x/3.1.x spec with x-google-api-management.mcp and deploy it with no extra infrastructure. The gateway accepts MCP JSON-RPC requests on a single /mcp endpoint, transcodes tools/call into the corresponding REST call, runs it through existing policies, and returns the response as an MCP result. Authentication via JWT or API key works unchanged for REST operations; tools/list is unauthenticated by default and requires JWT in production for security. With no separate server to operate, teams in Public Preview can expose up to 1,000 tools per gateway that support existing authentication and quota, and the MCP server is automatically discoverable via API hub and Agent Registry.
Databricks has announced general availability of the Genie One Model Context Protocol (MCP) server, now a managed service within Unity Gateway with centralized governance, fine-grained policies, and audit logging across every invocation. The MCP provides a single governed interface for any AI agent to access structured and unstructured data from Genie One, grounded in governed business context from Genie Ontology, eliminating agent sprawl and inconsistent answers. It exposes tools for asking questions, getting query results, checking incremental progress, and steering responses, with an optional MCP App for real-time interactive visualizations and Genie Ontology citations. Connected agent clients automatically interpret domain semantics via Genie Ontology across relational data and document repositories without custom connectors. Use cases include enriching slide creation with richer data, bringing customer usage context to outreach agents, and integrating business definitions into developer workflows, as noted by GetYourGuide.
Business leaders often have access to plenty of data but still cannot get a reliable answer to a simple question like why net revenue declined 8% at their largest account last week. The answer may span sales, finance, promotions, inventory, and account data, with each source potentially correct in isolation yet different in definitions, detail, relationships, and authority. Without the right business context, general-purpose agents cannot reliably determine what metrics mean, which sources are authoritative, how data should connect, or what each user is allowed to see. Genie One MCP gives governed context to any MCP-compatible AI agent, connecting assistants like ChatGPT, Claude, Microsoft Copilot, and coding agents to Genie One. This lets them answer business questions using approved definitions, trusted data relationships, and permission-aware access controls, with traceable, permission-aware answers grounded in governed business context.
The article demonstrates extending Red Hat OpenShift Lightspeed by integrating the Red Hat Satellite MCP server and bring your own knowledge (BYOK). The Satellite MCP server exposes live operational data, such as kernel versions, CVEs, and errata, through the Model Context Protocol. BYOK enriches the assistant with private enterprise knowledge, enabling retrieval-augmented generation (RAG) to combine internal documentation with infrastructure data. The integration requires installing the OpenShift Lightspeed operator and deploying the Satellite MCP server in the openshift-lightspeed project. Authentication is handled by storing the header value in a Secret, and the MCP server expects clients to include appropriate Accept headers for the text/event-stream media type.
Stripe implemented WebMCP on its Checkout UIs, which processes around 0.45% of global GDP, to optimize the buying experience for AI agents. Previously, agents relied on slow browser automation, consuming an average of 1.8 million tokens and 38.83 tool calls per transaction, taking over 2.5 minutes. WebMCP exposes MCP tools from the client side, allowing agents to execute actions like get_order_summary or fill_payment_form instead of interpreting the DOM. The implementation uses progressive tool disclosure, revealing only relevant tools; in evaluations across six models, agents using WebMCP consumed 42% fewer tokens, made 38% fewer tool calls, and completed checkout 39% faster. Stripe reused existing UI state and forms via imperative and declarative APIs, avoiding a separate agent-only code path and keeping human and agent experiences aligned.
Resend announced a headless dashboard initiative to make all dashboard capabilities available programmatically via the MCP, CLI, and API. Recent releases include the Email Metrics API for deliverability and engagement data, a Headless Webhook API for listing events and replaying deliveries, and a Cancel Broadcast API. The Duplicate Broadcast API copies any broadcast into a draft, and the Share Email API provides expiring read-only email links. The team aims to make the dashboard best-in-class while committing to full headless operation for every future entity. Developers can start building today by connecting the MCP server or using the CLI.
Dropbox has launched a modernized API documentation site at https://docs.dropboxapi.com, rebuilt to make integration faster and more intuitive. The new documentation features interactive API testing that lets developers set parameters, issue API calls, and view real responses from the Dropbox API directly in their browser without switching tools. An embedded AI assistant offers instant help with endpoint questions, troubleshooting, and code examples, while the documentation integrates with MCP (Model Context Protocol) so AI tools like Claude Code and Cursor can access up-to-date API information. Through the MCP server at https://docs.dropboxapi.com/_mcp/server, developers can connect their AI assistants to answer questions, explore the API, and assist with integrations using information directly from the docs. The update delivers a clean, responsive, searchable interface that brings endpoints, types, schemas, and related documentation together, with improved navigation, and provides comprehensive information including detailed error responses, type definitions, and full request/response schemas.
Auth0 Agent Gateway is announced in beta as a Customer Identity and Access Management (CIAM) control plane for governing product-native, customer-facing AI agents in multi-tenant SaaS applications. It addresses a trust model involving organizations, delegated user access, customer consent, independently owned connected accounts, and cross-tenant data boundaries, rather than workforce-only identity. Positioned between an agent and its tools, the gateway evaluates each call using agent, user, and organization context; it uses Organizations, Agents as Principals, Token Vault, token exchange, tenant logs, and administrative controls. The described capabilities include short-lived agent-only tokens, user-scoped credentials, runtime tool authorization, audit logging with optional SIEM streaming, and an agent kill switch. Auth0 is seeking product and engineering teams to join the beta.
AiChemy is a multi-agent assistant for cross-disciplinary research that combines external MCP servers including OpenTargets, PubChem, and PubMed with Databricks-managed chemical libraries. It can identify disease targets and drug candidates, retrieve chemical and pharmacokinetic properties, assess safety and toxicity, and attach findings to verifiable data sources. Its guided workflow covers disease-to-target-to-drug discovery and literature validation, while a vector search over a 250,000-molecule ZINC15 index uses 1024-bit ECFP embeddings to find compounds similar to Elacestrant. To build a custom supervisor, users connect public MCP servers, transform structured drug data into a Genie space, and index unstructured chemical data for similarity search. They can assemble it with no-code Agent Bricks or deploy a Langgraph supervisor with Lakebase, MLflow AgentServer, and a React interface; invocations are logged and traced through MLflow using OpenTelemetry standards.
DHI Group needed to move generative AI efforts beyond proofs of concept because its traditional software development lifecycle took months, while it sought faster delivery, technical validation, and broader AI literacy. AWS and DHI used a four-phase Hackathon Acceleration Package—preparation, enablement, a three-day build event, and a path to production—with workshops on Amazon Bedrock AgentCore, AI-DLC, and Kiro. Twenty participants formed three teams and produced prototypes for employer analytics, intelligent candidate matching, and a unified ClearanceJobs–AgileATS marketplace; DHI leadership committed to advancing all three toward production. The winning marketplace uses an MCP server, Amazon Bedrock AgentCore, Lambda functions, session memory, and Claude 3.5 Haiku to let recruiters search candidates and enrich profiles through natural-language requests. The post concludes that time-boxed, cross-functional hackathons can compress ideation, architecture, prototyping, executive alignment, and production planning when production criteria and preparation are established upfront.
Google describes partnering with Speakeasy to open-source the OpenAPI code-generation suite used for new SDKs for its Interactions, Agents, and Webhooks APIs. The change follows the May 2026 shutdown of a proprietary SDK-generation provider, which exposed platform risk while Google was preparing the Interactions API for general availability; migration prioritized avoiding breaking changes and preserving type definitions, strict error hierarchies, and streaming behavior. The AGPLv3 suite generates statically typed libraries for Python, TypeScript, Go, Java, C#, PHP, and Ruby, plus standalone agent-native CLI binaries and documentation MCP servers built from OpenAPI specifications and Markdown. Google says a deterministic generator paired with Antigravity AI agents now supports its pipeline across six targets, including three released SDKs, with roughly one engineer maintaining it, while generated code can remain under a chosen license such as MIT or Apache 2.0.
Preparing a Blender scene for robotics simulation requires more than exporting attractive assets: the world needs semantic labels, simulation-aware materials, sensors, collision geometry, physics properties, and validation against a target profile. The described workflow uses Codex or Claude as an orchestration agent, NemoClaw to coordinate specialized Hermes subagents, and NVIDIA Omniverse Libraries to inspect, modify, render, and validate the scene. Blender MCP supplies a structured inventory, while OpenUSD becomes the shared scene contract; ovphysx handles physics authoring and checks, and ovrtx produces visual preflight views. Safe mechanical repairs can be automated, but ambiguous choices such as semantic labels or physical behavior are escalated to a human, with follow-up checks run after approved changes. The intended handoff is a simulation-ready USD world for NVIDIA Isaac Sim or NVIDIA Isaac Lab.
Version 2026.2.2 of ReSharper, Rider, and .NET tools is available through the products, Toolbox App, or website. Rider adds an AI Agent Setup widget to the bottom-right status bar, where users can review supported MCP tools, skills, and hooks, see which are enabled, and open the relevant settings. Its hooks now give agents narrower inspection results for newly added code, while the Reformat file hook reports IDE formatting changes as a diff; dotCover also adds TUnit coverage, requiring JetBrains.dotCover.Framework and Microsoft.Testing.Platform 2.3.0 or later. The release fixes a macOS backend-resume freeze, removes dependence on Unity editor executable names for attachment, and enables MCP file operations across attached solution folders; ReSharper also receives TUnit coverage support.
AI agents running on laptops or clusters may inherit broad filesystem, network, and credential access, making faulty permissions or prompt injection potential security risks. The guide uses Red Hat OpenShift to build layered controls around an OpenClaw agent: namespace isolation, default-deny network policy, ResourceQuota, and optional Kata Containers contain workloads and limit escape or resource abuse. SPIFFE and SPIRE issue rotating SVIDs based on workload attributes such as namespace and ServiceAccount, allowing services to verify an agent without shared secrets. Governance adds OPA Gatekeeper admission policies, an MCP Gateway with risk-tiered tool authorization, NeMo Guardrails for prompt and completion filtering, and MLflow traces for auditability. The recommended rollout starts with namespace isolation and quotas, then adds sandboxing, identity, and the more involved governance controls.
The August ClickStack update covers five releases, v2.34 through v2.38, with dashboards as the main focus. Dashboard variables are generally available, letting filters supply selected values to raw SQL, builder fields, Lucene, and PromQL queries, while chained filters can narrow one another. Charts add formulas for combining series, a metrics explorer previews emitted metrics, and release markers align service versions with events such as latency spikes. The update also introduces the TimeSeries engine and PromQL support in private preview for Managed ClickStack and experimentally in open source, alongside a beta LLM observability dashboard, alerting improvements, OIDC collector authentication, and MCP server changes, including up to ten notification targets, alert names and tags, evaluation history through the API, and richer webhook payloads.
Harbor addresses a gap in Stripe’s AI-assisted workflows: designers needed dynamic information to assess stripe.com designs, but could not always justify a full engineering prototype. Built initially by one engineer in about 40 days, it lets designers describe an idea and use Stripe design systems and realistic mock data to generate shareable, browser-based prototypes without understanding code. Its agent writes a multi-file source tree, while Drydock compiles and renders React and TypeScript in the viewer’s browser; the agent can inspect pages, interact with elements, switch viewports, and iterate before publishing a single snapshot. Since May 2026, more than 3,000 Stripes have created 12,000 prototypes, and Harbor now integrates with other AI tools through MCP and Drydock’s standalone rendering contract, although live data and prototype-scoped state remain future goals.
Enterprise LLMs can hallucinate when they lack company-specific vocabulary and documentation, so the guide builds a bank agent grounded in internal data. It configures Red Hat OpenShift AI 3.5 Technology Preview features, enables OGX, AutoRAG, and the MCP catalog, and deploys PostgreSQL, Milvus, and MinIO for metadata, vector embeddings, and artifacts. AutoRAG processes documents, evaluates pipeline configurations against a benchmark dataset, and identifies a preferred setup; the example uses Qwen3-8B and embeddinggemma-300m models. A MariaDB MCP server adds access to customer records, with a patch supplying writable logging storage and a warning that unrestricted ALLOWED_HOSTS is for demo/development only. The resulting Streamlit agent answers a customer-information query and a Gold-card-limit question using RAG context and database tools.
Salesforce and Anthropic announced an expanded partnership making Claude a preferred model for Salesforce’s Agentforce platform, with availability aimed at customers in regulated sectors including financial services, healthcare, cybersecurity, and life sciences. Through Amazon Bedrock, Claude traffic will remain within Salesforce’s virtual private cloud and trusted environment, while industry-specific solutions are being developed beginning with financial services. The companies are also deepening Claude’s Slack integration through a Model Context Protocol server that can access channels, messages, and files for summaries, decisions, drafts, searches, and connected Salesforce CRM and Tableau insights. Salesforce is deploying Claude Code across its global engineering organization, and Anthropic uses Claude in Slack for internal sales workflows. Agentforce powered by Anthropic and the Claude-Slack bidirectional integrations are available today, while the regulated industry collaboration and Agentforce 360 integration for Claude remain under development.
Anthropic is expanding Claude for Financial Services with a beta Excel add-in, real-time data connectors, and six pre-built Agent Skills for finance workflows. Claude for Excel operates in a Microsoft Excel sidebar, where it can read, analyze, modify, debug, and create workbooks while tracking changes, explaining actions, and linking explanations to referenced cells. New connectors provide live or governed access to earnings events, portfolio data, internal data rooms, market data, credit research, and financial news through Aiera, Chronograph, Egnyte, LSEG, Moody’s, and MT Newswires. The six skills cover comparable company analysis, discounted cash flow models with WACC, scenarios, and sensitivity tables, due-diligence data packs, earnings analysis, and initiating coverage reports. Sonnet 4.5 scored 55.3% on Vals AI’s Finance Agent benchmark; these previews are available to Max, Enterprise, and Teams users, while Claude for Excel will gather feedback from 1,000 initial users.
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