all tools / ml
As of the latest check, Glimind tracks 200 ml AI agent (MCP) tools, of which 0 are healthy right now. The table below ranks them live-first by real-time reliability.
| tool | status | what it does | |
|---|---|---|---|
| run_llm llm_bridge_mcp | unknown | Send a prompt to an LLM and get a response. | alternatives |
| get_property_valuation Abhishekpendyala06/MCP Real Estate Intelligence Server | unknown | ML-backed property valuations using multiple approaches: Comparative Market Analysis, Cost Approach, Income Approach, Hybrid Ensemble, Sensi | alternatives |
| list_flows io.github.tjacquesson/llmtest-mcp | unknown | List all AI flows with cost and latency stats | alternatives |
| get_suggestions io.github.tjacquesson/llmtest-mcp | unknown | Get pending model-switch recommendations | alternatives |
| optimize_prompt io.github.tjacquesson/llmtest-mcp | unknown | Rewrite a flow's prompt and find a cheaper model that still works | alternatives |
| seed_samples io.github.tjacquesson/llmtest-mcp | unknown | Add test prompts for pre-launch benchmarking | alternatives |
| list_samples io.github.tjacquesson/llmtest-mcp | unknown | Show stored test samples per flow | alternatives |
| list_new_models io.github.tjacquesson/llmtest-mcp | unknown | Show new and trending models | alternatives |
| get_autopilot_status io.github.tjacquesson/llmtest-mcp | unknown | Check whether autopilot is on and whether the account is eligible | alternatives |
| disable_autopilot io.github.tjacquesson/llmtest-mcp | unknown | Turn off autopilot (existing optimizations stay active) | alternatives |
| run_benchmark io.github.tjacquesson/llmtest-mcp | unknown | Benchmark a flow against challenger models | alternatives |
| enable_autopilot io.github.tjacquesson/llmtest-mcp | unknown | Turn on weekly auto-optimization with safety gates + drift-based auto-revert | alternatives |
| verify_factuality_consistency Alpha-Park/genpark-multimodal-hallucination-factuality-verifier-skill | unknown | Ground-truth factuality validator & contradiction detector | alternatives |
| find_clinamen io.github.sebbsssss/clude | unknown | Anomaly retrieval: find memories that deviate from patterns. | alternatives |
| embed chrisfitzwilliam/machinetomachine_honeypot | unknown | Generate CPU-only text embeddings for input text | alternatives |
| ocr chrisfitzwilliam/machinetomachine_honeypot | unknown | Perform OCR on an image to extract text | alternatives |
| aeo_check marketing-mindset-mcp | unknown | Runs an AEO readiness audit with 23 weighted checks. | alternatives |
| similar io.github.renezander030/agentic-task-system | unknown | Semantically similar items (embedder-backed adapters). | alternatives |
| find_similar_code rdanieli/tentra-mcp | unknown | pgvector cosine ANN over agent-generated embeddings | alternatives |
| record_embedding rdanieli/tentra-mcp | unknown | Persist an agent-generated embedding vector | alternatives |
| compare io.github.religa/multi-mcp | unknown | Parallel multi-model analysis for architectural decisions or comparisons | alternatives |
| debate io.github.religa/multi-mcp | unknown | Multi-agent consensus workflow with independent answers and critique | alternatives |
| listModels @zapier/elevenlabs-connector | unknown | List models with capabilities and per-request character limits. | alternatives |
| list_voices groq/groq-mcp-server | unknown | List available TTS voices | alternatives |
| list_stt_models groq/groq-mcp-server | unknown | List available STT models | alternatives |
| analyze_image groq/groq-mcp-server | unknown | Analyze an image and return a description | alternatives |
| analyze_image_json groq/groq-mcp-server | unknown | Analyze an image and extract key information as JSON | alternatives |
| chat_completion groq/groq-mcp-server | unknown | Generate chat completions using Groq's LLM models | alternatives |
| transcribe_audio groq/groq-mcp-server | unknown | Transcribe audio file to text using Groq's STT models | alternatives |
| translate_audio groq/groq-mcp-server | unknown | Translate foreign language audio to English | alternatives |
| text_to_speech groq/groq-mcp-server | unknown | Convert text to speech using Groq's TTS models | alternatives |
| list_chat_models groq/groq-mcp-server | unknown | List available chat models | alternatives |
| get_voyage_forecast Cyreslab-AI/marinetraffic-mcp-server | unknown | Get the machine-learning voyage forecast for a vessel by MMSI or IMO number — predicted next port and ETA, combining live AIS position with | alternatives |
| embed io.github.tsilva/mcp-openrouter | unknown | Generate vector embeddings for a string or a list of strings, including optional encoding format and dimension controls. | alternatives |
| find_models io.github.tsilva/mcp-openrouter | unknown | Find matching model slugs by name or identifier and return a compact result set for fast selection. | alternatives |
| chat io.github.tsilva/mcp-openrouter | unknown | Send a prompt or multi-turn message array to any OpenRouter chat model, with sampling, JSON response, reasoning, provider routing, and assis | alternatives |
| list_models io.github.tsilva/mcp-openrouter | unknown | List OpenRouter models and filter by vision, image_gen, embedding, tools, or long_context. | alternatives |
| score_resume com.juicedresume/mcp | unknown | Score a resume against best practices. | alternatives |
| tailor_to_jd com.juicedresume/mcp | unknown | Tailor a resume to a job description. | alternatives |
| get_match_analysis livetennisapi/livetennisapi-codex-plugin | unknown | Model win probability and reasoning | alternatives |
| deliberation @policyrisk/mcp-server | unknown | Multi-LLM deliberation for high-stakes questions. | alternatives |
| predict_impact STiFLeR7/memex | unknown | Returns ranked list of likely affected modules based on graph coupling. | alternatives |
| deepagent_research wikidjon/openfinclaw | unknown | Run a full research → strategy → backtest loop from a natural-language query. | alternatives |
| segment_cells_2d cellpose-mcp | unknown | Segment cells in 2D images | alternatives |
| restore_and_segment cellpose-mcp | unknown | Combined restoration + segmentation | alternatives |
| segment_cells_batch cellpose-mcp | unknown | Batch process multiple images | alternatives |
| segment_cells_3d cellpose-mcp | unknown | Segment cells in 3D volumes | alternatives |
| denoise_image cellpose-mcp | unknown | Denoise microscopy images | alternatives |
| deblur_image cellpose-mcp | unknown | Deblur microscopy images | alternatives |
| upsample_image cellpose-mcp | unknown | Upsample low-resolution images | alternatives |
| train_segmentation_model cellpose-mcp | unknown | Train custom segmentation model | alternatives |
| train_restoration_model cellpose-mcp | unknown | Train custom restoration model | alternatives |
| list_available_models cellpose-mcp | unknown | List all pretrained models | alternatives |
| estimate_cell_diameter cellpose-mcp | unknown | Estimate cell diameter from image | alternatives |
| embedding mseep-workspace-qdrant-mcp | unknown | Generate or retrieve embeddings for text. | alternatives |
| list_bedrock_models claude-aws-mcp | unknown | List available foundation models (supports provider filter) | alternatives |
| invoke_bedrock_claude claude-aws-mcp | unknown | Invoke Claude model (default: Claude 3.5 Sonnet v2) | alternatives |
| invoke_bedrock_model_raw claude-aws-mcp | unknown | Invoke any Bedrock model with raw JSON | alternatives |
| dynamic_1d_equilibria mathmethods-mcp | unknown | Find and classify the equilibria of x' = f(x) | alternatives |
| dynamic_1d_bifurcation mathmethods-mcp | unknown | Equilibria vs parameter (bifurcation diagram) | alternatives |
| dynamic_2d_conservative_solve mathmethods-mcp | unknown | Divergence-free check, Hamiltonian/energy, closed orbits | alternatives |
| score_api api-ai-readiness | unknown | Score an API for AI-readiness from its OpenAPI/Swagger spec, returning a summary and a readiness:// handle for the full report. | alternatives |
| workflow_train_model xplainable/xplainable-mcp-server | unknown | Train a model using guided workflow | alternatives |
| workflow_wait_for_update xplainable/xplainable-mcp-server | unknown | Wait for a guided workflow update | alternatives |
| workflow_explain_model xplainable/xplainable-mcp-server | unknown | Explain a model | alternatives |
| workflow_deploy_model xplainable/xplainable-mcp-server | unknown | Deploy a model | alternatives |
| workflow_predict xplainable/xplainable-mcp-server | unknown | Make predictions with a model | alternatives |
| workflow_optimise_model xplainable/xplainable-mcp-server | unknown | Optimise a model | alternatives |
| workflow_create_report xplainable/xplainable-mcp-server | unknown | Create a report | alternatives |
| workflow_decide xplainable/xplainable-mcp-server | unknown | Make a decision in guided workflow | alternatives |
| models_train_model xplainable/xplainable-mcp-server | unknown | Train a model server-side | alternatives |
| models_get_feature_info xplainable/xplainable-mcp-server | unknown | Get feature information for a model | alternatives |
| models_refit_model xplainable/xplainable-mcp-server | unknown | Refit a model for hyperparameter tuning | alternatives |
| eval_toxicity multivon-mcp | unknown | QAG-graded toxicity / harmful-content detection. | alternatives |
| eval_bias multivon-mcp | unknown | QAG-graded bias across gender, race, politics, age, socioeconomic axes. | alternatives |
| eval_hallucination multivon-mcp | unknown | QAG-graded hallucination — does the output contain content NOT in context? | alternatives |
| eval_relevance multivon-mcp | unknown | QAG-graded answer-vs-question relevance. | alternatives |
| eval_answer_accuracy multivon-mcp | unknown | QAG-graded semantic equivalence vs ground truth. | alternatives |
| eval_context_precision multivon-mcp | unknown | RAG retrieval quality — are the retrieved chunks on-topic? | alternatives |
| eval_g_eval multivon-mcp | unknown | G-Eval flexible scoring. | alternatives |
| eval_custom_rubric multivon-mcp | unknown | Score against your own list of yes/no quality checks. | alternatives |
| eval_compare_runs multivon-mcp | unknown | Diff two eval report JSONs — pass-rate delta, per-case regressions/improvements, McNemar p-value. | alternatives |
| eval_faithfulness multivon-mcp | unknown | QAG-graded faithfulness — is a RAG output grounded in the retrieved context? | alternatives |
| eval_tool_call_accuracy multivon-mcp | unknown | Deterministic agent tool-call correctness. No LLM. | alternatives |
| eval_vqa_faithfulness multivon-mcp | unknown | Image-grounded visual-QA faithfulness. | alternatives |
| eval_document_grounding multivon-mcp | unknown | Multi-page document-grounded faithfulness for document-AI agents. | alternatives |
| eval_ingest_trace multivon-mcp | unknown | Normalize an agent trace from LangGraph / OpenAI Agents SDK / manual shapes for use with agent evaluators. | alternatives |
| agent djtelicloud/UniGrok | unknown | Leaf labor tool for multi-step agentic work; accepts a Mission Brief and returns densified results with cost receipts. | alternatives |
| grok_reflect djtelicloud/UniGrok | unknown | Focused structured critique for plans, code-review notes, outputs, and architecture decisions. | alternatives |
| chat djtelicloud/UniGrok | unknown | Plain Grok chat with optional model pinning and session history. | alternatives |
| chat_with_vision djtelicloud/UniGrok | unknown | Image analysis. | alternatives |
| chat_with_files djtelicloud/UniGrok | unknown | Grounded answers over uploaded xAI files. | alternatives |
| submit_research_job djtelicloud/UniGrok | unknown | Deferred xAI research job submission. | alternatives |
| get_research_job djtelicloud/UniGrok | unknown | Retrieve a deferred xAI research job. | alternatives |
| list_research_jobs djtelicloud/UniGrok | unknown | List deferred xAI research jobs. | alternatives |
| chat irad-bouzidi/mcp-ollama-account-rotation | unknown | Send chat completion request | alternatives |
| generate irad-bouzidi/mcp-ollama-account-rotation | unknown | Send text generation request | alternatives |
| list_models irad-bouzidi/mcp-ollama-account-rotation | unknown | List available models | alternatives |
| fluxus_spice_characterize cogitan-mcp | unknown | Characterizes SPICE-level circuit parameters for SFQ cells. Costs 1 call from Fluxus quota. | alternatives |
| fluxus_resonator_fr cogitan-mcp | unknown | Predicts resonator frequency for a given geometry. Costs 1 call from Fluxus quota. | alternatives |
| fluxus_sfq_predict cogitan-mcp | unknown | Predicts SFQ circuit margins and delays using surrogate models. Costs 1 call from Fluxus quota. | alternatives |
| fluxus_qem cogitan-mcp | unknown | Predicts the Hamiltonian for a TransmonCross + claw cell using the cQED surrogate. Costs 1 call from Fluxus quota. | alternatives |
| fluxus_qem_cross cogitan-mcp | unknown | Predicts the Hamiltonian for a TransmonCross cell (variant). Costs 1 call from Fluxus quota. | alternatives |
| fluxus_inv_cross cogitan-mcp | unknown | Inverse prediction: given target Hamiltonian parameters, returns geometry. Costs 1 call from Fluxus quota. | alternatives |
| run_fem_analysis maximedns5/freecad-mcp | unknown | Run the CalculiX solver on an existing Fem::FemAnalysis and return summary results. | alternatives |
| analyze_ticket_tool StanleyXisco/TicketAI | unknown | Analyzes an IT support ticket and returns category, urgency, summary, suggested response, and suggested assignee group. | alternatives |
| list_models openrouter-mcp | unknown | List all models with optional modality filter and sorting | alternatives |
| get_model openrouter-mcp | unknown | Get detailed info for a specific model by ID | alternatives |
| compare_models openrouter-mcp | unknown | Compare multiple models side by side | alternatives |
| derive_route_shard Aicent-Stack/iqa-mcp | unknown | Derive the ROUTE_SHARD / intent shard for an authority: SHA-256, first 16 bytes, hex. | alternatives |
| servicex_mcp.serve servicex-mcp | unknown | Starts the ServiceX MCP server (stdio transport) for a given backend, exposing ServiceX data-delivery operations as MCP tools. | alternatives |
| evaluate_skill hermify-mcp | unknown | Manually trigger the LLM Judge to score a draft and auto-transition state. | alternatives |
| check_blender_mcp_status JohanScheepers/Blender-to-Antigravity | unknown | Verifies the add-on handshake and returns the active scene details. | alternatives |
| analyze_scene_outliers JohanScheepers/Blender-to-Antigravity | unknown | Analyzes the scene and lists objects with highest polygon count but smaller size from the camera point of view. | alternatives |
| query_objects_by_material JohanScheepers/Blender-to-Antigravity | unknown | Finds which objects in the file are using a specified material. | alternatives |
| document_geometry_nodes JohanScheepers/Blender-to-Antigravity | unknown | Explains the main geometry nodes setup, adds inline documentation with frame elements, and creates a Text data-block. | alternatives |
| count_tokens io.github.rccola990-cloud/mcp-token-optimizer | unknown | Token count for any text + input cost across common models (or one model). | alternatives |
| estimate_cost io.github.rccola990-cloud/mcp-token-optimizer | unknown | Per-call and monthly/yearly spend for a prompt, model, output size, and call volume. | alternatives |
| slim_prompt io.github.rccola990-cloud/mcp-token-optimizer | unknown | Safely compresses a prompt and reports tokens and dollars saved. | alternatives |
| compare_model_costs io.github.rccola990-cloud/mcp-token-optimizer | unknown | Costs the same prompt across many models and recommends the cheapest one. | alternatives |
| transcribe_audio audo-ai/audo-mcp | unknown | Speech to text, who said what: 60 languages, SRT and VTT captions, word times. | alternatives |
| translate_to_english riteshhbhandari/yt-mcp-server | unknown | Translates the transcript to English | alternatives |
| extract_topics riteshhbhandari/yt-mcp-server | unknown | Extracts topics from the transcript using Gemini | alternatives |
| apex_twitter Apex-Foundation/copilot-mcp | unknown | Audience-quality scan. Real KOLs vs purchased followers, engagement rate, Apex-network fund overlap | alternatives |
| apex_score Apex-Foundation/copilot-mcp | unknown | 0-100 composite scoring across team, traction, tokenomics, market, security. 85+ shortens the path to a real Apex engagement | alternatives |
| laya_classify ocha-no-taiko/laya-mcp-server | unknown | 汎用の分類エンジン。choice/score/noulの質問を自由に定義して投げる | alternatives |
| laya_route_task ocha-no-taiko/laya-mcp-server | unknown | タスク仕分け用の固定質問セット（task_type/urgency/needs_human_review） | alternatives |
| unload_model @tmhs/local-ai-mcp | unknown | Evict a model from memory. | alternatives |
| list_models @tmhs/local-ai-mcp | unknown | Installed models across detected providers (or one provider). | alternatives |
| list_loaded @tmhs/local-ai-mcp | unknown | Models currently resident in memory. | alternatives |
| model_info @tmhs/local-ai-mcp | unknown | Detailed metadata for a model. | alternatives |
| pull_model @tmhs/local-ai-mcp | unknown | Download a model. Heavy: may transfer multiple GB. | alternatives |
| remove_model @tmhs/local-ai-mcp | unknown | Delete a model from disk. Destructive: requires confirm: true and a provider (no fan-out); refuses without confirm: true. | alternatives |
| benchmark @tmhs/local-ai-mcp | unknown | Measure latency and tokens/sec with one small completion. Heavy: runs real inference. | alternatives |
| load_model @tmhs/local-ai-mcp | unknown | Load a model into memory (Ollama keep_alive; LM Studio lms load). | alternatives |
| suggest_model @tmhs/local-ai-mcp | unknown | Recommend a model for a task, ranked by what fits your detected hardware. | alternatives |
| complete @tmhs/local-ai-mcp | unknown | Delegate a completion (streams via MCP progress when the client sends a progressToken). | alternatives |
| embed @tmhs/local-ai-mcp | unknown | Delegate embedding generation to a local model. | alternatives |
| fit_check @tmhs/local-ai-mcp | unknown | Whether weight + KV-cache estimate fits in free VRAM (GPU) or RAM (CPU). | alternatives |
| decompose_task Alpha-Park/genpark-autonomous-task-dag-decomposer-skill | unknown | Decomposes a complex task into a directed acyclic graph (DAG) of subtasks with dependency resolution | alternatives |
| list_operators @manturhub/cli | unknown | 列出所有可用的 AI 算子 | alternatives |
| run_operator @manturhub/cli | unknown | 调用指定的 AI 算子 | alternatives |
| beans_added io.github.syamaner/coffee-roaster-mcp | unknown | Detect when beans are added to the roaster (automatic T0 detection) | alternatives |
| first_crack_detection io.github.syamaner/coffee-roaster-mcp | unknown | Detect first crack from audio input using the ONNX model | alternatives |
| seeany_refine_prompt juin20260102-oss/seeany-sun-mcp | unknown | 用 AI 润色商品图提示词，返回优化后的提示词，Live 模式可能收费。 | alternatives |
| seeany_generate_product_image juin20260102-oss/seeany-sun-mcp | unknown | 创建商品图异步任务，返回 job_id 和初始状态，Live 模式会产生费用。 | alternatives |
| seeany_get_generation juin20260102-oss/seeany-sun-mcp | unknown | 查询单个任务的最新状态，返回状态、输出 URL、错误信息。 | alternatives |
| seeany_wait_generation juin20260102-oss/seeany-sun-mcp | unknown | 轮询任务直到完成或超时，返回最终状态和输出列表。 | alternatives |
| seeany_get_capabilities juin20260102-oss/seeany-sun-mcp | unknown | 查询模型、比例、分辨率和当前运行模式，返回模型与能力列表。 | alternatives |
| discover_estimators sktime-mcp | unknown | Discover sktime estimators matching a query or filter. | alternatives |
| describe_estimator sktime-mcp | unknown | Get detailed description and metadata for a specific estimator. | alternatives |
| instantiate_estimator sktime-mcp | unknown | Create an estimator instance with given parameters. | alternatives |
| save_model sktime-mcp | unknown | Save a fitted estimator to a file. | alternatives |
| load_model sktime-mcp | unknown | Load a fitted estimator from a file. | alternatives |
| brainstorm_quick io.github.spranab/brainstorm-mcp | unknown | Instant multi-model perspectives in under 10 seconds | alternatives |
| brainstorm io.github.spranab/brainstorm-mcp | unknown | Multi-round debate between AI models (API or hosted mode) | alternatives |
| brainstorm_collect io.github.spranab/brainstorm-mcp | unknown | Submit model responses in a hosted session | alternatives |
| brainstorm_debate io.github.spranab/brainstorm-mcp | unknown | Multi-round AI brainstorming debate across multiple models with structured synthesis | alternatives |
| watch io.github.rbmuller/scherlok | unknown | Detect anomalies in the data | alternatives |
| apartment-hunter-score ai-engineers-guild/Apartment Hunter MCP Server | unknown | Score an apartment listing using LLM based on renovation, furniture, and user preferences. | alternatives |
| get_stats io.github.spanlens/mcp-server | unknown | Aggregate cost, request count, token usage, latency, error rate. Optional groupBy for per-model or per-provider breakdown. | alternatives |
| query_requests io.github.spanlens/mcp-server | unknown | Individual LLM requests with cost, latency, model, error message. Filter by model, provider, status, userId, since, limit. | alternatives |
| get_savings io.github.spanlens/mcp-server | unknown | Model-swap recommendations with projected monthly savings and adoption status. | alternatives |
| claude_panel claude-consult-mcp | unknown | Multi-perspective verification in one call; N perspectives = N Claude runs | alternatives |
| score_icp_fit mambalabsdev/mcp-icp-fit-scorer | unknown | Scores a company against your ideal customer profile, returning a 0-100 score, A-D tier, and per-signal breakdown. | alternatives |
| ai_summarize_text Br0ski777/ai-summarizer | unknown | Summarize raw text into key points | alternatives |
| ai_summarize_url Br0ski777/ai-summarizer | unknown | Fetch a URL and summarize its content | alternatives |
| tournament.evaluate samalbanese/mcp-tournament | unknown | Evaluate 1-4 models across scenarios and a judge panel, producing ranked results. | alternatives |
| tournament.quick_test samalbanese/mcp-tournament | unknown | Run a fast smoke score with one scenario and one judge. | alternatives |
| tournament.leaderboard samalbanese/mcp-tournament | unknown | Get the best cached score per model across runs. | alternatives |
| read_screen_text avicuna/Screen Vision MCP Server | unknown | OCR text extraction from screen | alternatives |
| understand_screen avicuna/Screen Vision MCP Server | unknown | AI-powered screen analysis | alternatives |
| analyze_image avicuna/Screen Vision MCP Server | unknown | Analyze a dropped/AirDropped image file | alternatives |
| models am0y/fal | unknown | List available models with optional pagination | alternatives |
| search am0y/fal | unknown | Search for models by keywords | alternatives |
| generate am0y/fal | unknown | Generate content using a model | alternatives |
| snapgen-mcp snapgen-ai/snapgen-devtools | unknown | A stdio bridge to the hosted SnapGen MCP server for clients that only launch local commands. | alternatives |
| auto_classify @teralynk/mcp-server | unknown | Use AI to automatically classify a file's sensitivity level (public, internal, confidential, restricted) | alternatives |
| remediation_plan @teralynk/mcp-server | unknown | Generate an AI-powered step-by-step remediation plan for compliance issues | alternatives |
| run_agent ThinkFlowLab/system1-agents | unknown | Run a System 1 agent on a task | alternatives |
| decide ThinkFlowLab/system1-agents | unknown | Make a single decision given options and state | alternatives |
| predict_insurance_premium insurance-predict-mcp | unknown | 보험료를 예측합니다. | alternatives |
| get_model_info insurance-predict-mcp | unknown | 모델의 정보를 반환합니다. | alternatives |
| validate io.github.aidc2026ai-melon/aidc-mcp-server | unknown | Run electrical, cooling, layout, safety, and data rule checks. | alternatives |
| design io.github.aidc2026ai-melon/aidc-mcp-server | unknown | Size an AI data center with rack count, PUE, MVA, cost, and timeline. | alternatives |
| vestige_backfill samvallad33/vestige | unknown | Reaches backward through memories to find causal chains leading to a failure, using Retroactive Salience Backfill | alternatives |
| check_agent_creative_orientation mcp-coaia-sequential-thinking | unknown | Detect and correct bias in reasoning orientation | alternatives |
| get_task runapi-ai/@runapi.ai/gpt-image-2-mcp | unknown | Fetch the current status and latest payload for an existing task. | alternatives |
| execute_prompt FirenzeClaw/kimi-debug-tunnel | unknown | 发送 prompt 并等待完整回复，默认排除思考链 | alternatives |
| ask_local_ollama remixms029g/sbtu-mcp-server | unknown | Send a prompt to a local Ollama instance via REST API (with CLI fallback) and return the response. | alternatives |
| token_count mcp-context-guard | unknown | Estimate token count (word-based heuristic) | alternatives |
| doctor DoppiaG93/ctxmem | unknown | Check the semantic (Ollama) backend end to end with fix-it hints | alternatives |
| bench DoppiaG93/ctxmem | unknown | Measure token and premium-request savings for a query | alternatives |
| salud_diodo iortizfigueroa/Leaseir MCP Server | unknown | Predicción de rotura de un diodo (calibraciones COMP) | alternatives |
| admin_get_ticket_ai_reply EaseCation/ec-usercenter-mcp-server | unknown | Get AI reply for ticket | alternatives |
| analyze_meal io.github.mrfentmen/nutritionix-mcp | unknown | Nutrients for free-text meals with totals. | alternatives |
| bitrix24_call_transcribe paskal/bitrix24-mcp-server | unknown | Default tier transcription using Whisper large-v3, punctuated, readable, raw segments (no speaker labels) | alternatives |
| bitrix24_call_transcribe_max paskal/bitrix24-mcp-server | unknown | Max tier transcription using GigaAM + Whisper + pyannote, returns both transcripts + speaker-tagged turns | alternatives |
| bitrix24_call_transcribe_fast paskal/bitrix24-mcp-server | unknown | Fast tier transcription using GigaAM v2, ~5x real-time, raw lowercase, no punctuation, no speaker labels | alternatives |
| nanmesh.entity.verify io.github.sacravenger/nanmesh-mcp | unknown | Run verification pipeline on a product | alternatives |
As of the latest check, Glimind tracks 200 ml AI agent (MCP) tools, of which 0 are healthy right now. The table below ranks them live-first by real-time reliability. Glimind rates each neutrally (0–100) from safe liveness probes plus privacy-clean real-usage outcomes — see each tool's live page for its current score and a working alternative if it's down.
Ranked live-first by current verdict (healthy → degraded → down), then by the neutral reliability score. Glimind sells no tools, so the ranking is unconflicted.
Every tool here links to its live alternatives — capability-matched substitutes that are healthy now. Or query https://glimind.com/v1/alternatives/{toolId}.
Live data via MCP/REST. Neutral ratings — Glimind only measures.