Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@My Quant — Editorial Discovery what MCP tools are available?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
The public editorial and advertising front door for the Liquidity Lab family: Seiche, LiquiLens, and LiquiLens—Undertow.
The site consumes each product's structured editorial feed at build time. Its
SOURCE_PUBLISHED website mode gives every record the source marks published a
MyQuant reading page, while preserving the specialist's canonical URL, exact
claim, evidence clocks, fingerprint, and limitation. The mobile app feed is
independently SUSPENDED and contains zero stories.
Every specialist page must also pass the analysis-quality gate. It answers what
the source says, what changed (or why a comparison is unavailable), why the
mechanism matters, what to inspect next, and where the evidence stops. The JSON
Feed carries the same change/next-check fields and its PASSED receipt. A build
fails instead of publishing thin labels, missing source identity, missing clocks,
or known invalid comparison grammar.
data/fleet-registry.json maps the complete registered family at an immutable
LiquiLens family.toml revision: seven core repositories, six research modules,
and ten adjacent surfaces. Coverage does not imply ingestion. Only LiquiLens,
Seiche, and Undertow market-liquidity currently publish compatible direct
readings; upstream, research, private, paused, delivery, and separate-domain
projects remain visible at /coverage with their exact reason.
The public site has two explicit lanes:
Interpreted: plain-English readings of Seiche, LiquiLens, and Undertow work;
MyQuant Analysis: independently sourced house reporting on important news.
The Interpreted lane includes reviewed longforms and LiquiLens historical case
files. Case files display each lens's HIT, MISS, or VOID separately and
state whether the replay was reconstructed later. They are not silently
promoted into real-time calls or validated-backtest evidence.
Original house reporting lives in content/ and must declare its sources,
contribution, limitations, and publication status.
npm test
MYQUANT_USE_REVIEWED_CACHE=1 npm run build
npm run verify
npm run devThe build has no runtime dependencies. If a source is temporarily unavailable,
it uses the last successful data/cache.json slice for that source and prints the
coverage state in the generated page. The LiquiLens desk channel is additionally
pinned to liquilens.desk-bit-feed.v1; a missing or changed root schema is treated
as an upstream contract failure, so the build keeps the last accepted channel and
marks LiquiLens as cached/degraded instead of normalizing an unknown shape.
The product exposes read-only discovery without accounts or user state:
GET /api/v1/capabilities describes the editorial, feed, and evidence surfaces;
GET /api/v1/health returns a non-sensitive compatibility heartbeat;
POST /mcp serves five stateless, read-only tools: discovery, health,
bounded latest stories, exact stable-ID retrieval, and evidence-aware search;
GET /openapi.json is the curated REST contract;
GET /.well-known/ai-catalog.json and GET /.well-known/mcp.json expose
public AI/MCP discovery, with the Registry manifest at GET /server.json.
The product version (0.1.0), REST contract (myquant.editorial/1.1), and
MCP server (2.1.1 available) stay distinct. Content tools read the canonical
public /feed.json, validate its full publication/evidence contract, retain
source and release fields, and cap each list/search response at 20 records.
Use latest_stories for a chronological overview, search_stories to find
records by text, and get_story with a stable ID returned by either list tool.
Search normalizes Unicode and whitespace, matches every space-separated term
as a case-insensitive substring, and returns matches newest first. It does not
perform semantic search or interpret quotation marks and Boolean operators.
The tools return the archive's evidence clocks and limitations; a successful
health check does not establish that its market evidence is current.
Public health also reports Vercel's exact deployed Git SHA when available,
allowing scheduled smoke and Registry publication to bind the live endpoint to
a reviewed commit.
Registry verification builds with MYQUANT_USE_REVIEWED_CACHE=1; this uses
the committed evidence receipt instead of pulling a different editorial wire
after the release SHA has already been selected.
The MCP endpoint supports the current per-request protocol metadata as well as
the listed legacy protocol handshakes. Legacy Mcp-Session-Id headers are
accepted for compatibility but never create server-side sessions. Cross-origin
MCP requests are limited to the configured MyQuant site origin; the REST
metadata remains public and cacheable.
The deployed Streamable HTTP endpoint is
https://myquantdoesntspeakenglish.com/mcp.
No API key is required for these public read-only tools. Connect through the
Glama remote connector
or a compatible MCP client. The separate
Glama repository listing
tracks source licensing and optional Glama-hosted releases; a repository scan
is distinct from inspection of the deployed remote connector.
Related MCP server: MCP Multi-Server Gateway
First-party software is available under the MIT license. The license does not cover editorial articles, collected data, third-party content, media, or branding. Fonts retain their existing SIL Open Font License notices. RIGHTS.md describes these boundaries. Installing the software or reading the MCP does not grant additional rights to its underlying sources.
Model output never enters the network build or scheduled sync path. An operator may import one immutable, already-validated candidate with:
npm run app-copy:import -- \
--packet /absolute/path/evidence-packet.json \
--candidate /absolute/path/draft.json \
--validator /absolute/path/validation.json \
--review /absolute/path/public-copy-review.jsonThe importer checks exact file hashes, source ID and fingerprint, evidence
packet and validator bindings, support pointers, shadow-only authority, immutable
teacher/model revisions, and two-reviewer adjudication. A source revision makes
the copy ineligible immediately: the website uses its deterministic
SOURCE_GROUNDED explanation and the app edition omits the record. See
docs/APP-COPY-IMPORT.md for the review receipt contract.
The scheduled sync evidence wire workflow checks seven upstream publication
channels at
02:17, 08:17, 14:17, and 20:17 UTC. A changed evidence fingerprint produces one
small content commit, which becomes the deployment trigger; an unchanged network
produces no commit and no redeploy. Frequency is a check cadence, not a quota.
Automation may collect and normalize published records. It may not manufacture a
fact, silently infer calm from a missing feed, or publish a house investigation
without the source and evidence fields described in content/README.md.
Website archive mode is an operator distribution instruction, not a claim that
every source record received legal or regulatory clearance. Corrections,
retractions, canonical links, content boundaries, and the emergency stop remain
active. The homepage uses a first-party silent cinema cut derived from the
approved app launch creative and documented in assets/media/. Third-party
field recordings are explicitly excluded from the published build.
Check that this endpoint responds with product.health.v1 metadata: product, API/MCP versions, deployed source SHA when available, and checked_at. Use for connection and version diagnosis; it does not fetch the editorial feed or prove source freshness. Public and read-only; no credentials or arguments. Use list_capabilities for supported surfaces and content limits.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only and idempotent behavior, and the description adds useful context beyond them: it is public, requires no credentials, and reports version/deployment metadata. It also sets expectations by stating it does not prove source freshness, which prevents over-interpretation of the health status.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short, purposeful sentences front-load the core behavior and return content, then cover usage, limitations, and alternatives. No sentence is wasted or redundant with the annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-argument read-only health check, the description fully covers what the tool returns, when to use it, what it does not do, and where to go for related capabilities. Even without an output schema, the key response fields are enumerated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty and additional properties are disallowed, so there are no parameters to document. The description reinforces this by explicitly stating 'no credentials or arguments,' which removes any ambiguity about hidden or required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: checking that the health endpoint returns product.health.v1 metadata. It also lists the exact fields returned and differentiates itself from feed-fetching tools, so an agent can identify its purpose immediately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use it for connection and version diagnosis, and clarifies what it does not do—fetch the editorial feed or prove source freshness. It also names list_capabilities as the alternative for supported surfaces and content limits, giving clear routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve one published story using its exact stable ID from latest_stories or search_stories. Returns story, feed receipt, and release identity while retaining canonical sources, evidence clocks, publication state, release IDs, and limitations. Matching is exact and case-sensitive; an unknown ID returns a tool error. Public and read-only; no credentials. The canonical feed is cached for up to 60 seconds; unavailable or invalid feeds return a tool error. Use search_stories first when you only know a title or topic.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Exact stable story id copied from a list/search result, including its prefix; not a title or URL. Case-sensitive, nonblank, without surrounding whitespace, at most 256 characters. |
| Name | Required | Description |
|---|---|---|
| feed | Yes | |
| story | Yes | |
| schema | Yes | |
| release | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description goes further by adding concrete behavioral details: exact case-sensitive matching, unknown IDs returning a tool error, public/no-credentials access, 60-second feed caching, and errors for unavailable or invalid feeds. This goes well beyond the annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and is reasonably compact. Most sentences earn their place, though the phrase about 'canonical sources, evidence clocks, publication state, release IDs, and limitations' is dense and somewhat jargon-heavy for a one-parameter retrieval tool, especially since an output schema is already present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only retrieval tool, the description is complete: it explains the ID provenance, exact matching, error behavior, caching, credentials, and how to route to search_stories when necessary. Since an output schema is present, the description does not need to enumerate return fields in more detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the id parameter thoroughly, including exactness, prefix, case-sensitivity, whitespace, and length constraints, so schema coverage is 100%. The description reinforces the exact-match behavior and mentions the unknown-ID error case, but it does not add substantial new parameter meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Retrieve'), a specific resource ('one published story'), and the exact identifier type ('exact stable ID'). It also distinguishes itself from search_stories by emphasizing direct retrieval by ID rather than topic/title search, so an agent can clearly tell them apart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to 'Use search_stories first when you only know a title or topic,' naming the alternative and the condition that selects it. It also clarifies that unknown IDs return a tool error, which guides the agent to avoid calling get_story with approximate or unverified identifiers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read recent published archive records when you want a chronological overview without a search term. Returns count, stories, the feed receipt, and release identity; each story retains sources, evidence clocks, publication state, release IDs, and limitations. Public and read-only; no credentials. Lists default to 10 records, at most 20, without pagination. The canonical feed is cached for up to 60 seconds; unavailable or invalid feeds return a tool error. Use search_stories for text matching or get_story for an exact returned ID.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum records to return, newest first; 1–20, default 10. There is no pagination parameter. |
| Name | Required | Description |
|---|---|---|
| feed | Yes | Canonical feed URL, content hash, item count, publication authority, and retrieval timestamp. |
| count | Yes | Number of records returned, not the total number of matches. |
| schema | Yes | |
| release | Yes | MCP version and deployed source SHA, when available. |
| stories | Yes | Newest-first published records retaining stable IDs, source links, evidence clocks, publication state, release IDs, and limitations. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, open-world, and non-destructive behavior; the description adds meaningful context beyond that: public access with no credentials, default/maximum limits, no pagination, 60-second caching, and error behavior for unavailable or invalid feeds. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every sentence carries information: primary purpose, return contents, access model, limits, caching, error behavior, and alternatives. It is front-loaded with the core usage and does not waste words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single optional parameter, rich annotations, output schema, and sibling tooling, the description covers everything needed to invoke the tool correctly: input limits, output contents, safety profile, error cases, and when to choose a different tool. Nothing important is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, limit, is fully documented in the schema with default, minimum, maximum, and no-pagination semantics. The description repeats the default/maximum behavior without adding substantial new meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Read'), a clear resource ('recent published archive records'), and a clear use case ('chronological overview without a search term'). It explicitly distinguishes itself from siblings by naming search_stories and get_story as alternatives for other needs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: use this when you want chronology without a search term. It also names search_stories for text matching and get_story for exact IDs, which clearly routes an agent away from this tool when those conditions apply.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Discover available product features, API/MCP URLs, versions, content limits, and interpretation boundaries before choosing a content tool. Returns product.capabilities.v1 metadata, without fetching stories or checking upstream freshness. Public and read-only; no credentials or arguments. Use latest_stories for recent records or get_health for endpoint compatibility. The mobile app distribution channel remains separately suspended.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds meaningful behavioral context beyond them: it is public, requires no credentials or arguments, returns metadata only, and does not fetch stories or check upstream freshness. The separate mobile app suspension note also discloses an important scope limitation. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each carrying distinct information: purpose, return type and exclusions, authentication/argument requirements, and sibling routing. The most important usage context is front-loaded, and there is no fluff or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-argument, read-only metadata tool with no output schema, the description is complete: it states what is returned, what is intentionally not performed, access constraints, and which sibling tools cover adjacent use cases. An agent has enough context to decide to call it and interpret its result safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters and the schema already documents this with additionalProperties false. The description reinforces this by stating 'no credentials or arguments,' which is a useful confirmation, but the schema already carries the full semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Discover available product features, API/MCP URLs, versions, content limits, and interpretation boundaries.' It clearly distinguishes this tool from content-fetching siblings by stating it returns product.capabilities.v1 metadata 'without fetching stories or checking upstream freshness.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: use this tool 'before choosing a content tool,' and alternatives are named directly—'Use latest_stories for recent records or get_health for endpoint compatibility.' This tells an agent exactly when this tool is appropriate and when to route elsewhere.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find published archive records by text when you do not know an exact story ID. All space-separated terms must match as case-insensitive substrings across IDs, titles, summaries, tags, products, beats, evidence status, contributions, or source labels/release IDs. Returns newest-first stories, normalized query, count, feed receipt, and release identity, preserving evidence clocks and limitations. No relevance ranking or pagination; zero matches returns an empty list. Public and read-only; no credentials. The feed is cached for up to 60 seconds; invalid queries or unavailable/invalid feeds return a tool error. Use get_story for an exact ID or latest_stories for an unfiltered overview.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum matching records to return, newest first; 1–20, default 10. Does not change which terms must match. | |
| query | Yes | Plain text, for example "dollar funding" or a source release ID. Unicode NFKC-normalized, trimmed, and whitespace-collapsed; every term must match. At most 12 terms, 160 characters, and 512 UTF-8 bytes after normalization. No quote, Boolean, regex, or semantic-search syntax. |
| Name | Required | Description |
|---|---|---|
| feed | Yes | Canonical feed URL, content hash, item count, publication authority, and retrieval timestamp. |
| count | Yes | Number of records returned, not the total number of matches. |
| query | Yes | The Unicode-normalized query with leading/trailing whitespace removed and internal whitespace collapsed. |
| schema | Yes | |
| release | Yes | MCP version and deployed source SHA, when available. |
| stories | Yes | Newest-first published records retaining stable IDs, source links, evidence clocks, publication state, release IDs, and limitations. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint: false, and the description adds substantial behavioral context beyond that: public/no-credentials access, 60-second feed caching, error on invalid queries or unavailable feeds, newest-first ordering, and preservation of evidence clocks and limitations. It also explicitly states the absence of relevance ranking and pagination. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every sentence earns its place: matching semantics, result shape, behavior on empty/error cases, caching, and routing to siblings are all covered without filler. The primary action and trigger are front-loaded in the first sentence, followed by operational details an agent needs before calling.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, the annotations, and the output schema, the description is complete: it covers when to use it, what inputs mean, what outputs include, failure modes, caching, and alternatives. An agent has everything necessary to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description still adds valuable parameter semantics: it defines how query terms are interpreted (case-insensitive substrings, space-separated, all must match), the fields searched, normalization behavior, term/character/byte limits, and absence of quote/Boolean/regex syntax. It also clarifies that limit only caps results and does not change matching behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Find published archive records by text' and explicitly states the trigger condition 'when you do not know an exact story ID.' It also names sibling tools for contrast (get_story, latest_stories), so an agent can distinguish this tool from alternatives without inspecting their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: text search when the exact ID is unknown. It also names alternatives directly: 'Use get_story for an exact ID or latest_stories for an unfiltered overview.' It further notes no pagination and the empty-list behavior for zero matches, making invocation expectations clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v2.1.1get_healthget_storylatest_storieslist_capabilitiessearch_storiesScored across 5 tools
Each tool targets a clearly distinct capability: metadata discovery (list_capabilities), health/version diagnosis (get_health), chronological listing (latest_stories), exact-ID retrieval (get_story), and text search (search_stories). The descriptions explicitly cross-reference sibling tools ('Use search_stories for...', 'Use get_story for an exact ID'), removing ambiguity between the two metadata tools and between listing vs. searching. An agent can reliably select the right tool for a given intent.
Most tools follow a predictable verb_noun snake_case pattern (list_capabilities, get_health, get_story, search_stories). The outlier is latest_stories, an adjective_noun phrase with no verb, which slightly breaks the pattern. Otherwise the convention is consistent and readable.
Five tools is well-scoped for a read-only editorial discovery surface, with each tool earning its place (capabilities, health, list, get, search). No redundant or trivially thin endpoints, and no bloat. The set is tight and purposeful.
The surface covers the core read-only discovery lifecycle: discover capabilities, verify health, list recent stories, fetch by ID, and search by text. Minor gaps remain, such as no pagination beyond 20 records and no tag/beat browsing distinct from free-text search, but agents can work around these. Coverage is solid for the stated public, read-only purpose.
Trust, freshness, policy, and discovery layer for public MCP servers.
Agent-native registry to discover APIs, MCP servers and CLIs, with live health checks.
Guarded MCP server for agent-readable business truth, provenance, readiness, and discovery.
Scans remote MCP servers for protocol, security, and TLS issues; exposes scan tools via MCP.
