list_graphsio.github.piers-fawkes/fodda — Discover available knowledge graphs, metadata, and routing instructions.
brand_trackerio.github.piers-fawkes/fodda — Compile a comprehensive Brand Intelligence Profile across all knowledge graphs.
get_earnings_divergenceio.github.piers-fawkes/fodda — Detect deflections, gaps, and divergence between analyst concerns and executive responses in earnings calls.
get_earnings_intelligenceio.github.piers-fawkes/fodda — Query management commentary, business guidance, and Q&A from company earnings calls.
search_graphio.github.piers-fawkes/fodda — Hybrid keyword + semantic search across curated graphs for trend clusters and evidence.
search_statisticsio.github.piers-fawkes/fodda — Search for specific quantitative metrics, indicators, and numeric data points.
search_insightsio.github.piers-fawkes/fodda — Search expert quotes, qualitative signals, and professional interpretations.
get_label_valuesio.github.piers-fawkes/fodda — Discover valid values for a node label or category.
get_neighborsio.github.piers-fawkes/fodda — Traverse from seed nodes to discover related concept nodes and links.
get_nodeio.github.piers-fawkes/fodda — Retrieve detailed metadata, properties, and attributes for a single node by ID.
get_evidenceio.github.piers-fawkes/fodda — Retrieve source signals, articles, citations, and provenance for a trend or node.
discover_adjacent_trendsio.github.piers-fawkes/fodda — Find semantically similar trends to a given trend node.
get_domain_intelligenceio.github.piers-fawkes/fodda — Search all PSFK curated domain graphs (retail, beauty, sports, fashion, consumer electronics, F&B) in parallel.
get_expert_intelligenceio.github.piers-fawkes/fodda — Query specialist industry graphs built by leading strategists and experts.
get_report_intelligenceio.github.piers-fawkes/fodda — Search institutional report insights from DHL, PwC, Delta, and other partners.
deep_research_topicio.github.piers-fawkes/fodda — Launch an autonomous research session combining graphs with live web search.
check_research_statusio.github.piers-fawkes/fodda — Check progress or retrieve the final narrative report of a deep research job.
consult_analystio.github.piers-fawkes/fodda — Engage a Synthetic Analyst persona to
get_supplemental_contextio.github.piers-fawkes/fodda — Fetch macro context from up to 10 institutional data sources in a single query.
check_supplemental_statusio.github.piers-fawkes/fodda — Retrieve output from a supplemental context job.
list_analystsio.github.piers-fawkes/fodda — List available Synthetic Analyst expert personas.
ep_guard_actionio.github.emiliaprotocol/mcp-server — Requests policy evaluation and, when required, named-human signoff for the exact action.
ep_dispute_fileio.github.emiliaprotocol/mcp-server — File a dispute against a receipt.
ep_trust_gateio.github.emiliaprotocol/mcp-server — Check if a transaction with a counterparty should be allowed based on trust policy.
ep_create_delegationio.github.emiliaprotocol/mcp-server — Create a delegation authorizing an agent to act on behalf of a principal.
ep_submit_receiptio.github.emiliaprotocol/mcp-server — Submit a receipt after a completed task to update trust profile.
ep_check_signoffio.github.emiliaprotocol/mcp-server — Reports whether that authorization is pending, denied, approved but unspent, or consumed.
ep_trust_profileio.github.emiliaprotocol/mcp-server — Retrieve the full behavioral trust profile of an entity.
ep_install_preflightio.github.emiliaprotocol/mcp-server — Check if a plugin or app is safe to install based on policy.
ep_verify_receiptio.github.emiliaprotocol/mcp-server — Verifies the stored receipt and anchor through the configured EMILIA service.
glossary_searchio.github.eminegurcu/auditsocials-mcp — Search by keyword and/or category. Returns matching terms with short definitions.
glossary_defineio.github.eminegurcu/auditsocials-mcp — Define a term by name or slug. Returns the full definition, category, applicable platforms, related terms and persistent URI.
glossary_list_categoriesio.github.eminegurcu/auditsocials-mcp — List glossary categories with term counts.
show_critical_alertsgcp-mcp-fastmcp — Show all critical alerts from the last 24 hours
create_vpc_networkgcp-mcp-fastmcp — Set up a new VPC network with subnet
raster_convertgdal-mcp — Convert a raster file to a different format.
raster_reprojectgdal-mcp — Reproject a raster file to a new coordinate reference system.
raster_statsgdal-mcp — Compute statistics for a raster file.
vector_infogdal-mcp — Get metadata about a vector file.
find_agentio.github.enrichgateagent-png/beacon-mcp — Search agents by capability/task
top_agentsio.github.enrichgateagent-png/beacon-mcp — Most-starred / highest-reputation agents in the index
agent_detailsio.github.enrichgateagent-png/beacon-mcp — Full detail for one agent by id
memory_setio.github.enthrium/oe-mcp — Store a key-value pair in persistent memory
memory_getio.github.enthrium/oe-mcp — Retrieve a value from persistent memory by key
memory_listio.github.enthrium/oe-mcp — List all stored memory key-value pairs
memory_deleteio.github.enthrium/oe-mcp — Delete a memory entry by key
approve_chainio.github.enthrium/oe-mcp — Approve a manual agent chain execution
log_listio.github.enthrium/oe-mcp — List action log entries
log_cleario.github.enthrium/oe-mcp — Clear the action log
run_agentio.github.enthrium/oe-mcp — Execute an OE Runtime YAML agent
edit_treemodelchoice-mcp — Tweak an existing tree — change probabilities, payoffs, labels, or the objective, add or remove whole options/outcomes (add_option / add_bra
set_input_distributionmodelchoice-mcp — Make a tree input uncertain — put a ModelRisk Vose* distribution on a branch's cash flow or probability (like typing a distribution into the
build_control_panelmodelchoice-mcp — Lift the tree's inputs into a control panel at the top of the sheet — every probability and cash flow as a labelled cell, with the tree link
export_tree_jsonmodelchoice-mcp — Round-trip a tree's raw ModelChoice JSON — export to save/share/version.
import_tree_jsonmodelchoice-mcp — Round-trip a tree's raw ModelChoice JSON — import (validated) to write it back into a workbook.
import_precisiontreemodelchoice-mcp — Import a PrecisionTree workbook (.xls/.xlsx) into ModelChoice — converts a copy (original untouched). Drives MC_ImportPrecisionTree_Auto.
read_sheetmodelchoice-mcp — Read a result sheet's cells back (numbers / text), e.g. the robustness verdict or a sensitivity report.
build_treemodelchoice-mcp — Build a tree from a structured description and write it into Excel (dry-run by default). Validates + rolls it back so you confirm the recomm
open_workbookmodelchoice-mcp — Open a workbook (.xlsx) from disk in the running Excel so the other tools can act on it. Reports its sheets + any ModelChoice tree sheets; r
run_evpimodelchoice-mcp — Expected Value of Perfect Information for the active tree — the most you'd pay for perfect information before deciding. Drives ModelChoice's
run_risk_profilemodelchoice-mcp — The outcome distribution for each decision option — expected value, min, max, std dev, plus the cumulative-probability table. Shows downside
build_mcdamodelchoice-mcp — Build a multi-criteria (MCDA) model — for choices that aren't pure money. Give the tree + criteria (ordinal options, weights, direction), ag
close_workbookmodelchoice-mcp — Close an open workbook by file name (counterpart to open_workbook). Discards unsaved changes by default; pass save=True to save first.
list_treesmodelchoice-mcp — List the decision trees in a workbook with node-type counts.
get_treemodelchoice-mcp — Full structure of one tree — decision / chance / terminal nodes, branches, probabilities, values.
roll_upmodelchoice-mcp — Roll the tree back to its expected values and optimal policy — the decision recommendation, in plain English.
verify_rollbackmodelchoice-mcp — Cross-check our rollback against the MC_V_<id> cells ModelChoice itself wrote — a correctness guarantee when the tree has been rendered.
run_scenariosmodelchoice-mcp — What-if comparison — give named scenarios (bundles of input changes); each is rolled back and compared to the baseline (EV, optimal decision
run_utilitymodelchoice-mcp — Apply a risk attitude (utility function) — returns the certainty equivalent, risk premium, and the optimal decision under risk aversion (can
run_eviimodelchoice-mcp — Expected Value of Imperfect Information for a specific test — pass the target chance node and a likelihood matrix P(signal|state); returns E
run_decision_reportmodelchoice-mcp — Run a report — strategy_table, policy_suggestion, decision_brief, mcda_report, or force_to_outcome — and read it back (rows + label→value pa
run_analysismodelchoice-mcp — Run any decision-analysis (robustness, sensitivity, strategy_table, policy_suggestion, decision_brief, mcda_report, risk_profile, evpi) and
run_robustnessmodelchoice-mcp — Run the robustness ("break the decision") analysis and return a structured read — verdict, score, and the minimum input change that flips th
run_sensitivitymodelchoice-mcp — Run one-way sensitivity and return the tornado-ordered report (which assumptions the decision is most sensitive to) + baseline EV + sheets.
license_statusmodelchoice-mcp — Report the ModelChoice licence state (licensed / trial / expired / not activated). Building and analysis actions require a full licence; rea
generate_imagemodelscope-image-gen-mcp — Generate an image from a text prompt using ModelScope models
generate_imagemodelscope-image-mcp — Creates an image from a text prompt using the ModelScope async API.
generate_imagemodelscope-mcp-server — Generate images from text prompts or transform existing images using AIGC models
get_context_infomodelscope-mcp-server — Access current operational context including authenticated user information and environment details