> For the complete documentation index, see [llms.txt](https://docs.agenticflow.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.agenticflow.ai/changelog/office-hour-50-public-routes-and-model-updates.md). # Office Hour #50: Public Route Stability, Accessibility Sweep & MCP Reliability + Model Updates ### Quick Recap Office Hour #50 focuses on stability and usability improvements across MCP onboarding, public/workspace routes, and production-facing interaction flows, while adding new model options to the catalog. This release includes: * New model availability in PixelML and AgenticFlow * 7 practical Workflow Blueprint Prompts across unique business categories * Stability fixes for custom MCP authentication and tool discovery * Automatic token refresh for MCP connections when refresh tokens are still valid * Clearer prompts and workflow controls for MCP connection readiness before chat * Safer behavior for public routes and workspace entry surfaces * Keyboard/accessibility improvements for high-usage management and builder pages 🎥 Watch the full session: {% embed url="" %} *** ### What Changed & Why #### 1. New Models Added Across PixelML and AgenticFlow This release adds new model entries to expand execution options for workflows and agents: * `xiaomi/mimo-v2.5-pro` (PixelML) * `xiaomi/mimo-v2.5` (AgenticFlow) * `GLM5.2` (PixelML) * `mistralai/mistral-nemo` (AgenticFlow)
Model selector showing new AgenticFlow models including MiMo V2.5 and Mistral Nemo

New model options appear in the agent model selector.

Teams gain additional choices for balancing cost, speed, and quality in everyday builds. **Model Evidence Notes** The visuals below come from the model publishers or provider pages. They are useful for understanding why these models were added, but they should be read as external model evidence rather than AgenticFlow-run evaluation results. | Model | Surface | Why it matters | | ------------------------ | ----------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `xiaomi/mimo-v2.5-pro` | PixelML | Agentic coding and long-horizon tool-use model with 1M-token context. Xiaomi's model card lists a 1.02T-parameter MoE architecture with 42B active parameters. | | `GLM5.2` | PixelML | Long-horizon coding and agent model with 1M-token context and 128K max output, positioned by Z.ai around software engineering, MCP/tool-use, and multi-step automation workloads. | | `xiaomi/mimo-v2.5` | AgenticFlow | Native multimodal model with 1M-token context for image, video, audio, text, agent, and coding workflows. | | `mistralai/mistral-nemo` | AgenticFlow | Cost-efficient 12B open model option with 128K context and strong multilingual coverage for practical multilingual and lightweight agent workloads. |
Official MiMo V2.5 Pro benchmark chart showing agentic coding, software engineering, and long-horizon benchmark results

MiMo V2.5 Pro benchmark evidence from the official XiaomiMiMo model card. Source: XiaomiMiMo/MiMo-V2.5-Pro.

Official GLM 5.2 coding benchmark chart from Z.ai

GLM-5.2 coding and long-horizon benchmark evidence from Z.ai. Source: Z.ai GLM-5.2 guide.

Official MiMo V2.5 multimodal benchmark chart

MiMo V2.5 multimodal benchmark evidence from the official XiaomiMiMo model card. Source: XiaomiMiMo/MiMo-V2.5.

Official MiMo V2.5 coding benchmark chart

MiMo V2.5 coding benchmark evidence from the official XiaomiMiMo model card. Source: XiaomiMiMo/MiMo-V2.5.

Official Mistral NeMo multilingual benchmark chart

Mistral NeMo multilingual benchmark evidence from Mistral AI. Source: Mistral NeMo announcement.

#### 2. Custom MCP Connections Are More Reliable After Auth Several custom MCP setups could remain in an unstable state after OAuth, showing “Requires Auth” while tool discovery still failed. This release improves the connection handling and verification path for custom MCP clients so authentication and tool visibility align more consistently after setup. MCP clients now proactively refresh tokens when a valid refresh token is available, reducing manual refresh steps and lowering connection downtime.
Custom MCP server connected and active with its tools discovered

Custom MCP connections stay active with tools reliably discovered after auth.

For teams building with external MCP endpoints, this reduces setup confusion and makes onboarding more predictable in day-to-day operations. #### 3. Improved Chat and MCP UX for Agent Workflows To make onboarding and chat startup faster, two UX updates were added: * Agent workflows now surface clearer in-app guidance when a workflow requires an active MCP connection before chat can run.
Agent builder showing a missing-connection notice before chat can run

Agents now clearly flag when a required MCP connection is missing before chat.

* MCP toggles now include an explicit visible-value on/off state in the header controls when adding connections, so users can immediately see whether they are exposing values or running in masked mode.
Add New MCP form with a visible-value on/off toggle on header values

A visible-value toggle now shows whether header values are exposed or masked.

In addition, agent chat flow handling was updated so a new thread can be created automatically in context, rather than requiring users to manually create a fresh thread before continuing. Finally, the chat interface now consistently uses the correct chat version marker, addressing the prior mixed display of v1/v2 labels in some situations. #### 4. Public Route and Workspace Entry States Are More Deterministic Some public pages and entry surfaces could show incomplete states when permissions or content context were not resolved correctly. The platform now handles those edge cases more clearly so users are less likely to see broken shells or confusing behavior when entering: * Public text editor route * Admin area for non-admin access scenarios * Public tools listing and tool detail pages This brings the UI closer to a stable baseline for first-time checks and regular usage. #### 5. Interaction and Accessibility Polishing Across Core Pages This release also continues earlier accessibility work by improving the semantics and keyboard accessibility of frequently used interface controls across: * Workflows and workflow step controls * Datasets (create/list/detail) * Tasks and agent rows * Projects, API keys, audit logs, and marketplace actions * Drive list actions and shared dialog/import controls * Agent chat composer flow and connection-state messaging around required MCP links The behavior remains the same, but control paths are more consistent and easier to navigate with keyboard interaction. *** ### Bug Fixes Included * Fixed custom MCP setups that could still appear unauthenticated after successful OAuth flow completion * Fixed MCP tool visibility mismatches in edge auth/discovery states * Fixed frequent manual-token-refresh workflows by proactively refreshing MCP tokens when available and not expired * Fixed unclear chat startup behavior when users attempted to run a workflow without a required MCP connection * Fixed confusing on/off state visibility in MCP header controls when adding a new MCP connection * Fixed missing/incorrect chat version labeling in agent chat UI (v1/v2 visibility) * Fixed manual new-thread friction in agent chat by auto-creating a new thread when continuing an incomplete or stale thread state * Fixed public `/text-editor` behavior to avoid exposing unfinished scaffold content * Fixed non-deterministic admin and public route outcomes when access context is missing * Fixed `/tools` and `/tools/[toolId]` handling for missing data contexts * Fixed dataset detail handling when payload shape was incomplete or malformed * Improved keyboard accessibility and discoverability for icon actions across high-traffic workspace surfaces * Fixed a set of row and action controls to remove mouse-only interaction patterns in workflows, tasks, and dataset views #### Before/After Evidence Two of the bug-fix groups had clean before/after visual evidence available from the verification pass. **Custom MCP Auth & Tool Discovery** Before the fix, some OAuth-based custom MCP connections could return from provider authorization but still show `Authentication Required`, `Requires Auth`, and `0` tools.
Before fix: custom MCP connection shows Authentication Required, Requires Auth, and zero tools

Before: OAuth completed, but the MCP connection still required auth and exposed no tools.

After the fix, the same class of custom MCP connection can stay active and expose discovered tools.
After fix: custom MCP connection is active and tools are discovered

After: the MCP connection is active and discovered tools are available.

**Dataset Detail Route Stability** Before the fix, opening an existing dataset detail route could land on the generic error boundary.
Before fix: dataset detail route shows a Something went wrong error boundary

Before: dataset detail route crashed into the generic error boundary.

After the fix, the dataset detail route renders the dataset surface instead of crashing when payloads are incomplete or inconsistent.
After fix: dataset detail route loads without crashing

After: the dataset detail route loads without the generic crash state.

### 🚀 7 Workflow Blueprint Prompts Copy any prompt below into **Claude Code**, **Codex**, Cursor, or another AI coding agent with the **AgenticFlow CLI** installed to deploy a working workflow quickly. These examples cover seven distinct workflow categories: document processing, market risk, appointment recovery, sales operations, UX research, AI news digestion, and onboarding profile generation. #### 1. Invoice Archive Extraction Packet (`invoice-archive-extraction-pack`) Extract invoice metadata from an email, propose an archive filename and folder path, flag items that need review, and create finance handoff notes. This is a draft-only workflow; it does not upload files, send email, or write to external systems. > Using the AgenticFlow CLI, deploy the invoice-archive-extraction-pack blueprint. Use this invoice email: > > Subject: Invoice INV-2026-118 from Northstar Events Hi team, please find attached invoice INV-2026-118 for the June customer summit venue deposit. Vendor: Northstar Events Ltd. Amount: USD 4,850. Due date: 2026-06-20. PO: PO-8842. Thanks, > > Archive policy: Extract invoice metadata, classify the document, propose an archive filename and folder path, and list review flags. Draft only; do not claim Gmail search, Drive upload, FTP transfer, Google Sheets save, or external action occurred. > > Deploy, run once, show me the extracted metadata table, proposed archive filename, proposed archive folder, review flags, and finance handoff notes. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 2. Commodity Risk Brief Packet (`commodity-risk-brief-pack`) Analyze commodity market signals, assess simple price-movement context, and create an operational risk brief with drivers, impacts, non-trading actions, and clear limitations. > Using the AgenticFlow CLI, deploy the commodity-risk-brief-pack blueprint. Use these market signals: > > "Signal: Brent crude moved from 82.10 to 86.40 over 24h. Shipping: Red Sea delays reported. OPEC: no formal production change. News: refinery outage in one region. Internal exposure: logistics budget sensitive above 85." > > Risk policy: "Create operational risk brief with anomaly assessment, drivers, alert level, and non-trading actions. Do not provide investment advice or price predictions. Do not claim API fetch, OPEC report fetch, news feed fetch, Slack/email alert, dashboard write, or external action occurred." > > Deploy, run once, show me the executive summary, alert level, drivers, operational impacts, non-trading actions, and limitations. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 3. No-Show Appointment Recovery (`no-show-appointment-recovery`) Determine whether an appointment is a no-show, assess lead intent, package the recovery decision with timestamp context, and draft rescheduling outreach. > Using the AgenticFlow CLI, deploy the no-show-appointment-recovery blueprint. Use this appointment record: > > "Lead: Marcus Reed. Meeting: pricing demo. Scheduled: 2026-06-04 09:00 America/New\_York. Current time: 2026-06-04 09:45 America/New\_York. Lead score: 87. Last activity: downloaded enterprise pricing guide. Owner: Jenna. Reschedule link: " > > Recovery policy: "No-show if 30+ minutes past scheduled time. High intent if lead score above 75 or enterprise pricing activity. Send friendly reschedule message and alert owner for same-day follow-up." > > Deploy, run once, show me the no-show JSON, lead status, reschedule message, sales rep alert, same-day follow-up checklist, and escalation note. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 4. Service Package Recommendation Packet (`service-package-recommendation-pack`) Read a prospect inquiry, route it by budget band, and create a service-package recommendation packet with fit rationale, scoped deliverables, implementation plan, risks, next step, and email draft. > Using the AgenticFlow CLI, deploy the service-package-recommendation-pack blueprint. Use this inquiry: > > "Company: Northstar Clinics | Contact: Elena Ramos | Need: automate patient feedback reporting and executive dashboards | Timeline: launch pilot in 45 days | Budget: 18000 USD | Notes: wants compliance review and staff training" > > Package rules: "Basic: under 8000 USD, discovery and lightweight prototype. Standard: 8000-20000 USD, workflow design, dashboard, and training. Premium: over 20000 USD, integrations, governance, rollout support, and executive reporting. Draft recommendations only; do not claim email send, Sheets update, Calendar event, or external action occurred." > > Deploy, run once, show me the selected package, fit reason, scoped deliverables, implementation plan, email draft, next step, and risks. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 5. UX Research Plan Builder (`ux-research-plan-builder`) Turn a research brief and constraints into a leadership-ready UX research plan, including research questions, methods, participant profile, interview guide, survey questions, and approval checklist. > Using the AgenticFlow CLI, deploy the ux-research-plan-builder blueprint. Use this research brief: > > "Product: onboarding analytics dashboard. Audience: product managers at B2B SaaS companies. Hypothesis: users fail to act because activation metrics are scattered across too many tools. Decision: whether to build a guided onboarding insights module." > > Research constraints: "Timeline: 2 weeks. Sample: 8 customer interviews and 20 survey responses. Channels: existing customer advisory group and in-app intercept. Need a concise plan that can be approved by product leadership." > > Deploy, run once, show me the research questions, methods JSON, participant profile, interview guide, survey questions, approval checklist, and expected decision output. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 6. AI News Digest Packet (`ai-news-digest-pack`) Use a public news URL, filter for AI- or technology-relevant items, categorize and summarize them, and create a draft daily digest. > Using the AgenticFlow CLI, deploy the ai-news-digest-pack blueprint. Use this news URL: > > Digest policy: Extract AI or technology-relevant items, categorize them, and write a concise daily digest. Draft only; do not claim ScrapeGraphAI scrape, Google Sheets save, Gmail send, batch split completion, or external action occurred. > > Deploy, run once, show me the digest title, categorized item table, concise summaries, why-it-matters notes, and editor notes. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** #### 7. Verified User Profile Card (`verified-user-profile-card`) Take a user profile and visual style, validate the email, create an HTML profile card, render it as an image, and return delivery copy plus CRM/profile log fields. > Using the AgenticFlow CLI, deploy the verified-user-profile-card blueprint. Use this user profile: > > "Name: Alex Rivera. Email: . Role: RevOps Manager. Company: Northstar Analytics. Bio: Builds automated reporting systems for go-to-market teams." > > Profile style: "Professional member profile card, clean white background, navy accent, readable name and role, no external assets." > > Deploy, run once, show me the validated profile fields, profile card URL, delivery email copy, verification status, and CRM/profile log fields. > > Leave the workflow deployed. Print the Web UI link. One-line note: why this rung of the composition ladder? *** *** ### Get Started * **Try AgenticFlow free:** * **Latest changelog:** * **Join our Discord:** * **Found a bug?** Email with a reproducible case.