"Recommended helper server for automating TeX to Lean conversions in GRAD-5 repository" matching MCP tools:

• me.validation_history

  AI Design Blueprint Doctrine

  Pro/Teams — return the authenticated user's architect.validate run history with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every architect.validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE calling architect.validate again on the same repository — they tell you which principles regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• baselight_ping

  Baselight

  Simple ping test to verify MCP server is responding

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• read_strategy_list

  Arcadia Finance

  Get Arcadia LP strategies. Use featured_only=true for curated top strategies (recommended first call). Returns a paginated list with 7d avg APY for each strategy's default range. Increase limit or use offset for pagination. All APY values are decimal fractions (1.0 = 100%, 0.05 = 5%). For full detail on a specific strategy (APY per range width), use read_strategy_info.

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• careerproof_task_status

  CareerProof MCP

  Check the status of any async task. Returns status (pending/running/completed/failed), progress percentage, and current stage. When status='completed', fetch full results with careerproof_task_result. Recommended polling interval: every 5-10 seconds. The task_id comes from any async start tool (atlas_start_gem_analysis, atlas_start_batch_gem, atlas_start_report, atlas_start_dialogue_assessment, atlas_start_custom_eval_inference, etc.). Free.

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• vf_health

  VoiceFlip

  Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.

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• register_agent_poll

  prxhub

  Partner tool to register_agent. Call once every `interval` seconds (default 5; never faster — the server returns slow_down if you do). Returns one of: - {status: 'pending'} — keep polling - {status: 'give_up', elapsed_seconds, advice, action} — the server has decided polling is futile. STOP. See below. - {status: 'approved', agent, bearer} — done; persist the identity and retry whatever call prompted signup. - {error: 'access_denied' | 'expired_token' | 'slow_down' | ...} On success, save `bearer.access_token` as your CLI token. Use it as `Authorization: Bearer <token>` on every prxhub request. No other credential is needed — prxhub signs your bundles server-side. GIVE-UP IS NOT OPTIONAL. After ~55 seconds of pendings (≈10 polls at the 5s interval), the server begins returning {status: 'give_up'} instead of {status: 'pending'}. When you see give_up: STOP CALLING register_agent_poll. Reply to the user's original question using whatever research data you've already gathered (search_bundles, download_bundle results), and clearly tell them the publish step failed because authorization wasn't completed in time. Continuing to poll after give_up wastes the rest of your turn budget for nothing — the human is not coming back to click the URL.

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• investigate_question

  VaultCrux Memory Core

  Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.

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• search_endpoints

  Fiber AI

  Canonical API selection tool for endpoint discovery and ranking. Use this first to get the top recommended operations for a user intent. Supports optional constraints plus tag-scoped selection via preferredTags, excludedTags, or a curated tagPack key.

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• stake

  Blueprint Agentic Staking (Solentic)

  Stake SOL with Blueprint validator in a single call. Builds the transaction, signs it with your secret key in-memory, and submits to Solana. Returns the confirmed transaction signature. Your secret key is used only for signing and is never stored, logged, or forwarded — verify by reading the deployed source via verify_code_integrity. This is the recommended tool for autonomous agents.

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• ping

  nara-tour

  Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.

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• crypto_fx_rates

  Inferventis MCP Server

  Converts an amount between any cryptocurrency and fiat currency pair, or between two cryptocurrencies, using real-time exchange rates sourced from CoinAPI. Supports all crypto-to-fiat (BTC/USD, ETH/EUR), fiat-to-crypto (USD/BTC), and cross-crypto (BTC/ETH) conversions. Use crypto_fx_rates when the conversion involves at least one cryptocurrency and a specific amount must be converted. Prefer crypto_price when only the spot price of a coin in fiat is needed without converting a specific amount, or prefer crypto_price_lite for the same spot price with a minimal response schema. Prefer currency_convert or currency_fx_lite when both currencies are fiat — those tools use ECB/Frankfurter or mid-market rates and do not consume a CoinAPI quota. Requires a CoinAPI key to be configured on the server.

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• me.validation_history

  AI Design Blueprint

  Pro/Teams — return the authenticated user's architect.validate run history with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every architect.validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE calling architect.validate again on the same repository — they tell you which principles regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.

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• get_campaign_report

  discovery

  <tool_description> Get aggregated performance report for a media buy. Shows spend, impressions, clicks, conversions with time-series breakdown. </tool_description> <when_to_use> To check campaign performance metrics after activation. Supports period filtering and granularity control. </when_to_use> <combination_hints> list_media_buys → get_campaign_report for performance analysis. Pair with get_compliance_status for full campaign overview. </combination_hints> <output_format> Totals (spend, impressions, clicks, conversions) + time-series breakdown. </output_format>

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• setup_mmm

  mcp-server

  Configures a Marketing Mix Modeling (MMM) study for a project. **What is MMM?** Marketing Mix Modeling measures the real contribution of each marketing channel (Google Ads, Meta, etc.) on a KPI (leads, revenue, conversions), accounting for external factors (seasonality, holidays, promotions). **Recommended workflow:** 1. Use get_schema_context to discover the project's tables/columns 2. Generate input SQL queries (KPI, channels, exogenous variables) 3. **Validate each query before calling setup_mmm:** Use execute_query to run a COUNT(*) wrapper on each input query (e.g., SELECT COUNT(*) FROM (<query>)). If any query returns 0 rows, do NOT include it in setup_mmm — warn the user that the data source is empty and ask whether to proceed without it or fix the query. 4. Call setup_mmm with the validated SQL queries — the study is automatically launched after setup 5. Do NOT call run_mmm after setup_mmm: the first run is triggered automatically **Important:** run_mmm is only needed to RE-RUN an existing study later, not after initial setup. **Input queries format:** Each query must return a "time" column (DATE) and the requested metrics. - role="kpi": a "kpi" column (the target KPI) - role="channel": "spend" and "impressions" columns + channel_name - role="exogenous": columns named after the exogenous variables + columns[] **Granularity**: "weekly" is recommended (MMM standard). SQL should aggregate by week. **Important**: Adapt the SQL dialect to the project's data warehouse type (BigQuery, Snowflake, Redshift).

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• virtualsms_order_history

  sms

  List past orders with optional filters for status, service, country, and a lookback window in days. Returns up to 50 orders (server cap) ordered most-recent-first.

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• baselight_ping

  baselight

  Simple ping test to verify MCP server is responding

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• diagnose_sglang

  Sovereign AI Blog

  Validate an SGLang configuration for NVIDIA DGX Spark (GB10/SM121A). Pure pattern-matching against known failure modes documented in the Sovereign AI Blog. No inference, no external calls. Returns critical issues, non-fatal warnings, and a recommended baseline config. All parameters are optional; supply only what you have. With no inputs you get the recommended config and a 'unknown' verdict.

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• calculate_inverter_size

  VoltPlan Wiring Diagrams

  Calculate the recommended inverter size for running AC loads from a DC battery system. Accounts for continuous power, startup surge power (motors typically surge 2-3x), and includes a 25% headroom for the continuous rating. Returns the recommended inverter wattage and the DC current draw at system voltage.

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• files_get_base64

  DialogBrain

  Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.

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