Skip to main content
Glama

Server Details

Test crypto and TradFi-perpetual claims using recorded counts, baselines, and replay.

If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Unhealthy
Last Tested
Transport
Streamable HTTP
URL
Repository
edgedepthhq/edgedepth-research-mcp
GitHub Stars
3
Server Listing
EdgeDepth Research MCP Server

Frequently Asked Questions

Discussions

No comments yet. Be the first to start the discussion!

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables submitting claims and receiving Ed25519-signed, hash-chained verdicts resolved against real external ground truth, supporting resolvers like GitHub PRs, on-chain transactions, URL JSON, HTTP status, and Kalshi markets.
    97
    MIT
  • A
    license
    B
    quality
    A
    maintenance
    Verify a number before an agent asserts it — a Deflated Sharpe Ratio for backtest, plus eval-gap, subset-win, and judge-bias checks, with signed receipts anyone can verify offline.
    34
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Read-only crypto perps microstructure for AI agents: normalized cross-exchange market state (funding + multi-year percentile, OI, volume, CVD, order-book imbalance, liquidations, basis), OHLCV, 15-min state history, and measured conditional outcomes (historical base rates, not predictions) — 6 assets across Binance, Bybit, OKX and Hyperliquid, every metric with self-declared coverage and freshness
    MIT
  • A
    license
    B
    quality
    C
    maintenance
    Enables auditing and verification of algorithmic trading backtests from coding agents like Claude Code, Cursor, and Windsurf, including look-ahead bias detection, overfitting checks, and sealed audit proof verification.
    3
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: base_rate measures condition frequency, commonality analyzes feature agreement across moments, run_scan and run_cohort perform queries and comparisons, while interpret_prose, list_features, get_report, next_page, and snapshot_at handle interpretation, registry, reports, pagination, and state reading. No two tools overlap in function.

Naming Consistency4/5

Tool names mostly follow a verb_noun or descriptive noun pattern (run_scan, get_report, list_features, interpret_prose), with minor deviations like base_rate and commonality (nouns) and snapshot_at (verb_preposition). Overall consistent and readable.

Tool Count5/5

The 9 tools are well-scoped for a research platform: covering query execution (run_scan, run_cohort, base_rate, commonality), data discovery (list_features, snapshot_at), interpretation (interpret_prose), result retrieval (get_report), and pagination (next_page). Not bloated nor sparse.

Completeness4/5

Essential operations are covered: scanning, comparison, frequency analysis, feature listing, state inspection, report fetching, and prose interpretation. Minor gaps such as explicit report publishing or feature creation are absent, but these align with the platform's deterministic and registry-based design.